Dr. Pokkuluri  Kiran Sree

 Professor & Head, Department of CSE
Shri Vishnu Engineering College for Women, Bhimavaram
Email: drkiransree@gmail.com
Mobile:  +919493050794,+917093146795
Editor-in-Chief
International Journal of Parallel and Cloud Computing Research(PCCR)(USA)
   International Journal of Advanced Science and Research

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                         Bibliography

Dr. P. Kiran Sree Pokkuluri is a distinguished academician, researcher, author, administrator, mentor, and speaker with more than two decades of experience in teaching, research, innovation, and academic leadership in the fields of Artificial Intelligence and Computer Science Engineering. He currently serves as Professor and Head of the Department of Computer Science and Engineering at Shri Vishnu Engineering College for Women.

Dr. Kiran Sree obtained his Bachelor of Technology (B.Tech.) degree in Computer Science and Engineering from Jawaharlal Nehru Technological University and his Master of Engineering (M.E.) degree in Computer Science and Engineering from Anna University. He earned his Ph.D. in Artificial Intelligence from Jawaharlal Nehru Technological University Hyderabad, specializing in advanced Artificial Intelligence research and applications.

Further strengthening his research profile, Dr. Kiran Sree successfully completed his Postdoctoral Research (PDF) under the mentorship of Prof. Dr. Martin Margala, Director of the School of Computing and Informatics at University of Louisiana at Lafayette, and Dr. Prasun Chakrabarti, Director of Research at Sir Padampat Singhania University. This collaborative postdoctoral research resulted in five high-quality publications, including three Scopus-indexed papers and two reputed journal articles, one published in a Q2-ranked journal and another in an ESCI-indexed journal.

An accomplished author and researcher, Dr. Kiran Sree has authored fifteen textbooks for undergraduate and postgraduate engineering students in the areas of Artificial Intelligence, Machine Learning, Deep Learning, and related emerging technologies. He has published more than 250+ research papers in reputed international journals and conference proceedings. His research interests include Deep Learning, Big Data Analytics, Bioinformatics, Cloud Computing, and Artificial Intelligence applications.

Dr. Kiran Sree has also contributed significantly to innovation and intellectual property creation by filing and publishing fourteen patents in the domains of Deep Learning and Artificial Intelligence. His academic excellence and global professional standing led to his inclusion in Marquis Who’s Who in the World, USA, in 2012.

Throughout his distinguished career, Dr. Kiran Sree has received several prestigious national and academic honors for his remarkable contributions to engineering education, research, Artificial Intelligence, and academic leadership. His journey of recognition began with the Rashtriya Ratan Award – Certificate of Excellence in 2010 for outstanding achievements and promoting India–International cooperation. He is also a two-time recipient of the Bharat Excellence Award, presented by Dr. G. V. G. Krishnamurty.

Over the years, he has earned numerous accolades, including the Best Regius Professor of the Year (AI & BI) and the ITAP 2022 Award for excellence in innovative teaching practices and contributions to Artificial Intelligence and Business Intelligence education. His contributions to research and academic excellence were further recognized through honors such as the Aishwarya Memorial Research Excellence Award (2023), the Jyestha Acharya Award of Recognition (2023–24), and the Veteran Scholar of Excellence Award (2024) presented by the AIMER Society for excellence in AI and Engineering.

Dr. Kiran Sree also received the Bharat Education Excellence Award (BEEA 2K24) and the Deep Learning – Technology Visionary Award (2024) in recognition of his impactful contributions to deep learning technologies, engineering research, and academic innovation. In acknowledgment of his dedication to teaching, mentorship, and societal contribution, he was honored with the Dr. APJ Abdul Kalam National Pratibha Award in 2025 for contributions to literature, education, and social service, along with the Best Teacher Award (2025) from SERF India. Most recently, he received the Global Supervisor Award (2026) for excellence in academic and research supervision. These honors collectively reflect his sustained commitment to student success, research advancement, innovation, and excellence in higher education.

Dr. Kiran Sree has actively contributed to curriculum development and academic governance. He served as a Board of Studies (BOS) member for B.Tech. programs in Artificial Intelligence, Machine Learning, and Computer Science under Jawaharlal Nehru Technological University Kakinada during the years 2022, 2023, and 2024. In addition, he serves as a BOS member for several autonomous engineering colleges and universities across India, contributing to curriculum modernization aligned with emerging technologies and industry needs.

Demonstrating strong academic leadership and administrative capability, Dr. Kiran Sree previously served as Principal of N.B.K.R. Institute of Science and Technology, one of the oldest private engineering institutions in Andhra Pradesh, for two years. He also worked as Vice Principal of KIT-RCPM and HOD-CSEIT at Aditya Engineering College. His leadership significantly contributed to institutional growth, academic quality enhancement, and research development initiatives.

A passionate educator and inspiring speaker, Dr. Kiran Sree has delivered more than 100 keynote lectures, technical talks, Faculty Development Programs (FDPs), workshops, and webinars at national and international platforms on topics related to Artificial Intelligence, Deep Learning, innovation, and emerging technologies. He also serves as Faculty Champion for the University Innovation Fellows (UIF) program of Stanford University, where he mentors students in innovation, entrepreneurship, leadership, and design thinking.

Dr. Kiran Sree actively contributes to the global academic and research community as an Editor-in-Chief, Editorial Board Member, and Reviewer for several reputed international journals and conferences. He also serves as the Global Vice President of the World Statistical Data Analysis Research Association (WSA), contributing to the advancement of statistical and interdisciplinary research worldwide.

Dr. Kiran Sree has also demonstrated exceptional capability in securing research funding and promoting academic innovation through sponsored projects, Faculty Development Programs (FDPs), and International Conferences. He successfully received grants from All India Council for Technical Education (AICTE) under the ATAL scheme to organize Faculty Development Programs focused on emerging technologies and advanced research areas. In addition, he secured AICTE funding support for organizing an international conference aimed at fostering research collaboration, knowledge sharing, and innovation among academicians, researchers, and industry experts.

Further strengthening his contributions to innovation and entrepreneurship, Dr. Kiran Sree obtained a research and innovation grant worth ₹17 lakhs from Department of Science and Technology (DST) under the TIDE initiative for executing technology-driven innovation and entrepreneurial projects as a PI. These achievements reflect his strong commitment to promoting research culture, technological innovation, faculty development, and student-driven entrepreneurship in higher education.

 

His professional affiliations include senior membership in International Engineering and Technology Institute (IETI), United Association of Computer and Electronics Engineers (UACEE), and International Association of Computer Science and Information Technology (IACSIT). He is also a member of Computer Society of India (CSI), Institute for Computer Sciences Social Informatics and Telecommunications Engineering (ICST), and International Association of Engineers (IAENG).

With an unwavering commitment to academic excellence, innovation-driven education, impactful research, and student empowerment, Dr. P. Kiran Sree Pokkuluri continues to inspire students, researchers, and educators through his visionary leadership and dedication to advancing the fields of Artificial Intelligence and Computer Science Engineering.

 

  He is associated with.

Institute	Role
Shri Vishnu Engineering College for Women N.B.K.R.Institue of Science & Technology	Professor & Head, Dept of CSE Principal , (2 Years) HOD CSE, (2 Years) Chief Coordinator IIP Cell(18 Months) Chief  Warden-Hostels(6 Months)
BVC Engineering College	Professor, Dept of CSE,  Chief  Coordinator- Entrepreneurship Cell In-charge of Research and Development Cell
KITS-RCPM	Vice Principal, (6 Months) HOD CSE&IT, Professor Dept of CSE
Aditya Engineering College	Assistant Professor & HOD CSE,IT

 

                            

Speech as Principal

Placement Record Video Coverage

Citation Index of Prof P.Kiran Sree

Publications in Digital Library


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Publications in Cornell University Library

1.Text Book on CA

2.Text Book on Artificial Immune System Based Classifiers

3. Text Book on Impact of Artificial Intelligence on Bioinformatics

4. A Text Book on Deep Learning the Future of AI

Internet of things with Deep Learning for Societal Applications(Text Book)

Journal Publications

1.	Client-adaptive neural networks: A server-driven architecture for dynamic model partitioning in edge computing	Journal of Theoretical and Applied Information Technology	104(1), 82–97	2026
2.	Capsule enclosed coordinate attention based dual batch depthwise convolutional knowledge distillation model for drug-drug interaction prediction	Molecular Diversity	Article in Press	2026
3.	Paddy plant disease detection through image processing using deep learning	Proceedings on Engineering Sciences	8(1), 397–404	2026
4.	Opposition-based multi-objective ant colony optimization framework for sustainable retrofitting: time–cost–energy–risk trade-offs	Asian Journal of Civil Engineering	26(5), 2223–2239	2025
5.	Optimizing time and cost in construction under uncertainty: A fuzzy-driven NSGA-III optimization approach	Asian Journal of Civil Engineering	26(7), 3099–3114	2025
6.	Optimization of sustainable retrofitting using OBL-MOTLBO: A multi-objective approach to time, cost, and environmental trade-offs	Asian Journal of Civil Engineering	26(12), 5185–5203	2025
7.	Detection and avoidance of black-hole attack in mobile adhoc network using bee-ad-hoc on-demand distance vector	IAES International Journal of Artificial Intelligence	14(1), 822–832	2025
8.	A novel approach for watermarking medical images using electronic patient record data and a multi-bit-quantisation modulation method	International Journal of Intelligent Engineering Informatics	13(2), 156–178	2025
9.	Altered microbiome influence on the enteric neuromuscular system in amyotrophic lateral sclerosis (ALS)	International Review of Neurobiology	180, 95–123	2025
10.	Enhancing image segmentation accuracy using deep learning techniques	Journal of Advanced Research in Applied Sciences and Engineering Technology	49(1), 139–148	2025
11.	Integrating LSTM and CNN for stock market prediction: A dynamic machine learning approach	Journal of Artificial Intelligence and Technology	5, 168–179	2025
12.	DDINet: Drug–drug interaction prediction network based on multi-molecular fingerprint features and multi-head attention centered weighted autoencoder	Journal of Bioinformatics and Computational Biology	23(1), 2550003	2025
13.	DDINet: Drug-drug interaction prediction network based on multi-molecular fingerprint features and multi-head attention centered weighted autoencoder	Journal of Bioinformatics and Computational Biology		2025
14.	Adaptive fuzzy heuristic algorithm for dynamic data mining in IoT integrated big data environments	Journal of Fuzzy Extension and Applications	6(3), 615–636	2025
15.	Machine Learning-Based Prediction of Energy Consumption in Smart Buildings for Sustainable Energy Management	Journal of Information Systems Engineering & Management		2025
16.	Smart monitoring of livestock health and behavior with sensor-based deep learning optimized system	Journal of Wireless Mobile Networks Ubiquitous Computing and Dependable Applications	16(3), 219–240	2025
17.	High accuracy classification of Parkinson's disease detection using RNN-Graph-LSTM	Proceedings on Engineering Sciences	7(1), 309–318	2025
18.	A novel ALU using distributed arithmetic for real time signal processing application	Proceedings on Engineering Sciences	7(1), 319–328	2025
19.	BISEARCHINS-driven eco-friendly hybrid rideshare system for sustainable and efficient urban transportation	Proceedings on Engineering Sciences	7(3), 1991–2000	2025
20.	Disaster Management Based on Biodiversity Conservation Using Remote Sensing Data Analysis Using Machine Learning Model	Remote Sensing in Earth Systems Sciences		2025
21.	Marine life ecosystem analysis based on climate change detection using deep learning algorithms	Remote Sensing in Earth Systems Sciences	8(2), 545–554	2025
22.	Intelligent reasonable optimization for virtual machine provisioning in hybrid cloud using fuzzy AHP and cost-effective autoscaling	SN Computer Science	6(7), 753	2025
23.	Revolutionizing cardiac prediction based on Fog-Cloud-IoT integrated heart disease model	Scalable Computing		2025
24.	A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network	Scientific Reports	15(1), 17594	2025
25.	Navigating efficiency: Evaluating wireless ad hoc network protocols with NS-3	Sigma Journal of Engineering and Natural Sciences	43(3), 910–921	2025
26.	Augmented and virtual reality based human resource management and its impact on organizational sustainability	WSEAS Transactions on Business and Economics	22, 1034–1060	2025
27.	Urban air quality monitoring system enhanced by IoT for comprehensive deployment, data collection, and environmental impact analysis	WSEAS Transactions on Environment and Development	21, 374–402	2025
28.	Convolutional Neural Networks for Enhancing Clinical Decision-Making	Biomedical Journal of Scientific & Technical Research		2024
29.	Fuzzy horizon: Unveiling the fog of uncertainty with cognitive cartography and fuzzy logic fusion	Communications on Applied Nonlinear Analysis	31(8S), 128–146	2024
30.	3D Convolutional Neural Networks for Video Recognition	Communications on Applied Nonlinear Analysis		2024
31.	RSSI-based 3D wireless sensor node localization using hybrid T cell immune and lotus optimization	Computers, Materials and Continua	81(3), 4833–4851	2024
32.	A secured and energy-efficient system for patient e-healthcare monitoring using the Internet of Medical Things (IoMT)	Data and Metadata	3, 368	2024
33.	3D convolutional neural networks for predicting protein structure for improved drug recommendation	EAI Endorsed Transactions on Pervasive Health and Technology	10	2024
34.	Enhancing rainwater harvesting and groundwater recharge efficiency with multi-dimensional LSTM and clonal selection algorithm	Groundwater for Sustainable Development	25, 101167	2024
35.	An energy and temperature aware deep reinforcement learning workflow scheduler in cloud computing	IEEE Access	12, 163424–163443	2024
36.	A robust authentication and trust detection with privacy preservation of data for fog computing in VANET using adaptive deep neural network	IEEE Access	12, 161227–161246	2024
37.	Vehicular fog resource allocation approach for VANETs based on deep adaptive reinforcement learning combined with heuristic information	IEEE Access	12, 139056–139075	2024
38.	Multiclass osteoporosis detection: Enhancing accuracy with woodpecker-optimized CNN-XGBoost	International Journal of Advanced Computer Science and Applications	15(8), 903–914	2024
39.	A systematic review on drug-to-drug interaction prediction and cryptographic mechanism for secure drug discovery using AI techniques	International Journal on Artificial Intelligence Tools	33(8), 2450003	2024
40.	Enhancing Network Security: Leveraging Machine Learning for Intrusion Detection	Journal of Electrical Systems		2024
41.	Auto encoders with Cellular Automata for Anomaly Detection	Journal of Electrical Systems		2024
42.	Optimizing Breast Cancer Diagnosis with Advanced Deep Learning Techniques in Medical Imaging	Journal of Electrical Systems		2024
43.	Generic Framework for Vehicle Identification System with Deep Learning Models	Journal of Electrical Systems		2024
44.	Green AI revolution machine learning for environmental-friendly communication networks	Journal of Environmental Protection and Ecology		2024
45.	Collaborative intelligence for IoT: Decentralized net security and confidentiality	Journal of Intelligent Systems and Internet of Things	13(2), 202–211	2024
46.	Bridging the gap between technology and medicine through the revolutionary impact of the Healthcare Internet of Things on remote patient monitoring	Journal of Intelligent Systems and Internet of Things	13(2), 212–222	2024
47.	Investigation of medication reviews and the identification of adverse drug reactions using machine learning algorithms	Measurement: Sensors	33, 101240	2024
48.	Design and implementation of an dynamic IoT cloud based processing platform	Proceedings on Engineering Sciences		2024
49.	Design and implementation of a dynamic IoT cloud based processing platform	Proceedings on Engineering Sciences	6(4), 1813–1820	2024
50.	Streamlining task planning systems for improved enactment in contemporary computing surroundings	SN Computer Science	5(8), 993	2024
51.	Drug recommendation using recurrent neural networks augmented with cellular automata	BOHR International Journal of Internet of Things, Artificial Intelligence and Machine Learning		2023
52.	Deep Learning in Bioinformatics-Current Advances and Future Prospects	Biomedical Journal of Scientific & Technical Research		2023
53.	Machine Learning for Quality in Health Care: A Comprehensive Review	Biomedical Journal of Scientific & Technical Research		2023
54.	Deep Learning for Heart Attack Prediction	Biomedical Journal of Scientific & Technical Research		2023
55.	SLA based Workflow Scheduling algorithm in Cloud Computing using Haris Hawks optimization	EAI Endorsed Transactions on Scalable Information Systems		2023
56.	Digital image watermarking based on hybrid FRT-HD-DWT domain and flamingo search optimisation	International Journal of Computational Vision and Robotics	13(6), 573–598	2023
57.	Digital image watermarking based on hybrid FRT-HD-DWT domain and flamingo search optimisation (WOS)	International Journal of Computational Vision and Robotics		2023
58.	A Comprehensive Survey of Convolutional Neural Networks for Skin Cancer Classification and Prediction	International Journal on Recent and Innovation Trends in Computing and Communication		2023
59.	A Comprehensive Analysis on Risk Prediction of Heart Disease using Machine Learning Models	International Journal on Recent and Innovation Trends in Computing and Communication		2023
60.	Blockchain-Enabled On-Path Caching for Efficient and Reliable Content Delivery in Information-Centric Networks	International Journal on Recent and Innovation Trends in Computing and Communication		2023
61.	Crowd counting and anomaly detection from CCTV footages using deep learning augmented with cellular automata	Journal of Theoretical and Applied Information Technology	101(13), 5275–5278	2023
62.	An Effective Workflow Scheduling Algorithm in Cloud Computing Using Cat Swarm Optimization	ECS Transactions		2022
63.	Crop disease prediction with convolution neural network (CNN) augmented with cellular automata	International Arab Journal of Information Technology	19(5), 765–773	2022
64.	Digital image watermarking based on hybrid FRT-HD-DWT domain and flamingo search optimisation (WOS2)	International Journal of Computational Vision and Robotics		2022
65.	An Ontology-Based Approach to Enhance Explicit Aspect Extraction in Standard Arabic Reviews	International Journal of Computing and Digital Systems (IJCDS)		2022
66.	Pattern of poly pharmacy among geriatric patients in a tertiary care teaching hospital	Journal of Dr. YSR University of Health Sciences		2022
67.	Fog-based data analytics scheme using edge affinity-based management	NeuroQuantology		2022
68.	COVID-19 Hotspot Trend Prediction Using Hybrid Cellular Automata in India	Engineering Science & Technology		2021
69.	A secure cellular automata integrated deep learning mechanism for health informatics	International Arab Journal of Information Technology	18(6), 782–788	2021
70.	Deep convolution network for COVID-19 death rate prediction	I-manager's Journal on Information Technology		2020
71.	Framework for Environment Quality Monitoring Using Radial Support Vector Regression	Journal of Computational and Theoretical Nanoscience		2020
72.	A novel cellular automata classifier for COVID-19 trend prediction	Journal of Health Sciences	10(1), 34–38	2020
73.	A novel cellular automata classifier for COVID-19 prediction	Journal of Health Sciences		2020
74.	IN-MACA-MCC: Integrated multiple attractor cellular automata with modified clonal classifier for human protein coding and promoter prediction	Advances in Bioinformatics	2014, 261362	2014
75.	A Fast Multiple Attractor Cellular Automata with Modified Clonal Classifier Promoter Region Prediction in Eukaryotes	Journal of Bioinformatics and Intelligent Control		2014
76.	A Fast Multiple Attractor Cellular Automata with Modified Clonal Classifier for Coding Region Prediction in Human Genome	Journal of Bioinformatics and Intelligent Control		2014
77.	AIX-MACA-Y Multiple Attractor Cellular Automata Based Clonal Classifier for Promoter and Protein Coding Region Prediction	Journal of Bioinformatics and Intelligent Control		2014
78.	Cellular Automata in Splice Site Prediction	MOJ Proteomics & Bioinformatics		2014
79.	AIS-PSMACA: Towards Proposing an Artificial Immune System for Strengthening PSMACA: An Automated Protein Structure Prediction using Multiple Attractor Cellular Automata	Global Journal of Computer Science and Technology		2013
80.	AIS-PRMACA: Artificial Immune System based Multiple Attractor Cellular Automata for Strengthening PRMACA, Promoter Region Identification	SIJ Transactions on Computer Science Engineering & its Applications		2013
81.	An Efficient Parallel IP Lookup Technique for IPv6 Routers Using Multiple Hashing with Ternary marker storage	African Journal of Information & Communication Technology		2011
82.	Identification of promoter region in genomic DNA using cellular automata based text clustering	International Arab Journal of Information Technology	7(1), 75–78	2010
83.	Investigating an artificial immune system to strengthen protein structure prediction and protein coding region identification using the Cellular Automata classifier	International Journal of Bioinformatics Research and Applications	5(6), 647–662	2009
84.	Cellular Automata with Biological Sequence Analysis Approach to Robotic Soccer	International Journal of Computer Science and Applications		2009
85.	Identification of Protein Coding Regions in Genomic DNA Using Unsupervised FMACA Based Pattern Classifier	International Journal of Computer Science and Network Security		2008
86.	Exploring a novel approach for providing software security using soft computing systems	International Journal of Security and Its Applications	2(2), 51–58	2008
87.	Improving quality of clustering using cellular automata for information retrieval	Journal of Computer Science	4(2), 167–171	2008
88.	NTCA: A novel text clustering algorithm built on Cellular Automata based local search and K-Means algorithm for identifying the protein coding regions in genomic DNA	Research Journal of Biotechnology	3(3), 38–45	2008
89.	Power-aware hybrid intrusion detection system (PHIDS) using cellular automata in wireless ad hoc networks	WSEAS Transactions on Computers	7(11), 1848–1874	2008

All Publications- Year Wise

Publication List – Sorted by Year (Descending)

Total Publications: 231 | Date Range: 2008–2026

2026

1. Soni Sharmila, K., Thanga Revathi, S., & Sree, P. K. (2026). A systematic review on drug-to-drug interaction prediction and cryptographic mechanism for secure drug discovery using AI techniques [Corrigendum]. International Journal on Artificial Intelligence Tools, 33, 2450003. https://doi.org/10.1142/S0218213026920016

2. Kadimi, S. S., Revathi, S. T., & Sree, P. K. (2026). Capsule enclosed coordinate attention based dual batch depthwise convolutional knowledge distillation model for drug-drug interaction prediction. Molecular Diversity. https://doi.org/10.1007/S11030-025-11433-X

2025

1. Alzubi, J. A., Pokkuluri, K. S., & Arunachalam, K. (2025). A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network. Scientific Reports. https://doi.org/10.1038/S41598-025-02144-2

2. Babu, G. R., Chintalapati, P. V., & Maneesha, B. (2025). A secure and efficient cloud storage system using advanced encryption standard algorithm for data protection. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 598). Springer. https://doi.org/10.1007/978-3-031-77078-4_6

3. Chintalapati, P. V., Babu, G. R., & Anoch, B. (2025). Detection of autism spectrum disorder using optimized extreme learning machine technique. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 598). Springer. https://doi.org/10.1007/978-3-031-77078-4_22

4. Chandanan, A. K., Rani, M., & Roy, V. (2025). Revolutionizing cardiac prediction based on fog-cloud-IoT integrated heart disease model. Scalable Computing.

5. Dash, B., Macedo, V. D. J., Sethi, K. C., et al. (2025). Optimizing time and cost in construction under uncertainty: A fuzzy-driven NSGA-III optimization approach. Asian Journal of Civil Engineering. https://doi.org/10.1007/S42107-025-01364-1

6. Gudavalli, H., Kurada, R. R., & Pokkuluri, K. S. (2025). A comprehensive review of deep learning for disaster victim detection: Trends, challenges, and future directions. In Proceedings of ICAISS 2025. IEEE. https://doi.org/10.1109/ICAISS61471.2025.11041936

7. Harini, V., Srikanth, P., & Sree, P. K. (2025). Hybrid deep learning with multi-level context for pain assessment using physiological signals. In Proceedings of ICCSAI 2025. IEEE. https://doi.org/10.1109/ICCSAI64074.2025.11064490

8. Joshi, S., Mahanthi, B. L., & Sahu, R. (2025). Integrating LSTM and CNN for stock market prediction: A dynamic machine learning approach. Journal of Artificial Intelligence and Technology. https://doi.org/10.37965/JAIT.2025.0652

9. Kavita, K., Suresh Kumar, K., & Pokkuluri, K. S. (2025). Simulation and implementation of English speech recognition by NLP. In Integrating neurocomputing with artificial intelligence. Wiley. https://doi.org/10.1002/9781394335718.CH9

10. Khang, A., Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2025). Deep learning augmented with robotics in pipeline inspection and leak detection for the oil and gas industry. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-8156-4.CH013

11. Kusuma, A., Raju, P., & Pokkuluri, K. S. (2025). Uncertainty and explainability in AI for chronic kidney disease: A comprehensive review. In Proceedings of ICCMC 2025. IEEE. https://doi.org/10.1109/ICCMC65190.2025.11139940

12. Manusha, S., Varsha, N., & Elayaperumal, S. (2025). Altered microbiome influence on the enteric neuromuscular system in amyotrophic lateral sclerosis (ALS). International Review of Neurobiology. https://doi.org/10.1016/BS.IRN.2025.04.006

13. Murthy, B. S., Lakshmi, K. A., & Raju, P. J. R. S. (2025). AgroVisionNet: A deep convolutional framework for multivariate crop yield forecasting in heterogeneous environments. In Proceedings of ICCRTEE 2025. IEEE. https://doi.org/10.1109/ICCRTEE64519.2025.11052937

14. Murthy, B. S., Pbv, R. R., & Kumar, K. S. (2025). Hybrid security framework and machine learning based anomaly detection for machine-to-machine communications. In Proceedings of ICCRTEE 2025. IEEE. https://doi.org/10.1109/ICCRTEE64519.2025.11053023

15. Pala, S., Maddula, P., & Yadavalli, R. (2025). Detection and avoidance of black-hole attack in mobile adhoc network using bee-ad-hoc on-demand distance vector. IAES International Journal of Artificial Intelligence. https://doi.org/10.11591/IJAI.V14.I1.PP822-832

16. Pbv, R. R., Pokkuluri, K. S., & Karunasri, A. (2025). Ensemble fusion for enhanced malicious URL detection by integrating machine learning and deep learning techniques. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 597). Springer. https://doi.org/10.1007/978-3-031-77075-3_27

17. Pbv, R. R., Prasad, M., & Rao, B. V. (2025). An efficient sentiment classification model using fusion of BERT and deep learning RNN variants. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 597). Springer. https://doi.org/10.1007/978-3-031-77075-3_22

18. Pokkuluri, K. S. (2025). Machine learning-based prediction of energy consumption in smart buildings for sustainable energy management. Journal of Information Systems Engineering & Management, 10(13S). https://doi.org/10.52783/JISEM.V10I13S.2000

19. Pokkuluri, K. S., Awasthy, S. K., & M, U. A. S. (2025). Improving intrusion detection with fused IGAN-IDs and randomized tree classification for enhanced performance. In Proceedings of OTCON 2025. IEEE. https://doi.org/10.1109/OTCON65728.2025.11070937

20. Pokkuluri, K. S., Chandrasekar, A., & Saivaraju, A. (2025). Charting the course. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3373-1504-1.CH002

21. Pokkuluri, K. S., Chauhan, T. R., & Sethi, K. C. (2025). Opposition-based multi-objective ant colony optimization framework for sustainable retrofitting: Time–cost–energy–risk trade-offs. Asian Journal of Civil Engineering. https://doi.org/10.1007/S42107-025-01309-8

22. Pokkuluri, K. S., Jain, K., & Navanitha, D. (2025). A unified knowledge base for drug label analysis using learning models, NLP, and IoT tasks. In Proceedings of OTCON 2025. IEEE. https://doi.org/10.1109/OTCON65728.2025.11070706

23. Pokkuluri, K. S., Kumar Chandanan, A., & Bhatt, N. (2025). Deep learning-enhanced intrusion detection and privacy preservation for IIoT networks. In Proceedings of ICDCECE 2025. IEEE. https://doi.org/10.1109/ICDCECE65353.2025.11035784

24. Pokkuluri, K. S., Mangalampalli, S. S., & Usha Devi, N. S. S. S. N. (2025). Predicting oil reservoir behavior with convolutional neural networks. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-8156-4.CH009

25. Pokkuluri, K. S., Mounika, T., & Krishna, B. M. (2025). Disaster management based on biodiversity conservation using remote sensing data analysis using machine learning model. Remote Sensing in Earth Systems Sciences. https://doi.org/10.1007/S41976-024-00188-Y

26. Pokkuluri, K. S., Nagendra, D. P., & Manjunath, T. C. (2025). Optimization of sustainable retrofitting using OBL-MOTLBO: A multi-objective approach to time, cost, and environmental trade-offs. Asian Journal of Civil Engineering. https://doi.org/10.1007/S42107-025-01479-5

27. Pokkuluri, K. S., Phaneendra Varma, C. H., & Shalem Raju, P. J. R. (2025). Identification of different medicinal plants using machine learning and image processing. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 597). Springer. https://doi.org/10.1007/978-3-031-77075-3_7

28. Pokkuluri, K. S., Sarkar, P., & Roy, V. (2025). Intelligent reasonable optimization for virtual machine provisioning in hybrid cloud using fuzzy AHP and cost-effective autoscaling. SN Computer Science. https://doi.org/10.1007/S42979-025-04287-5

29. Pokkuluri, K. S., Sivanjani, M., & Rapaka, A. (2025). Deep learning-based detection of traffic accidents using CNN and VGG16 on accident and foggy image datasets. In Proceedings of ISACC 2025. IEEE. https://doi.org/10.1109/ISACC65211.2025.10969159

30. Pokkuluri, K. S., Sivakoti, R., & Usha Devi, N. S. S. S. N. (2025). Hate speech detection using recurrent neural networks (RNN). In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 599). Springer. https://doi.org/10.1007/978-3-031-77081-4_5

31. Pokkuluri, K. S., Subha, A. D. S., & Shalem Raju, P. J. R. (2025). Fake news detection using ML algorithms. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 599). Springer. https://doi.org/10.1007/978-3-031-77081-4_4

32. Pokkuluri, K. S., Gurujukota, R. B., & Murthy, P. T. S. (2025). Generative adversarial networks (GANs) for drug discovery. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 599). Springer. https://doi.org/10.1007/978-3-031-77081-4_21

33. Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2025). CNN's augmented with IoT for traffic optimization and signal regulation. In Proceedings of international conference on artificial intelligence and smart energy. Springer. https://doi.org/10.1007/978-3-031-74885-1_22

34. Pokkuluri, K. S., Usha Devi, N. S. S. S. N., & Elayaperumal, S. (2025). Enhanced oil recovery strategy prediction using temporal convolutional network. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-8156-4.CH003

35. Pokkuluri, K. S., Usha Devi, N. S. S. S. N., & Khang, A. (2025). Deforestation and forest monitoring with CNN and RNN. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3373-1399-3.CH008

36. Prasad, M., Ajita Lakshmi, K., & Murthy, Ch. S. V. V. S. N. (2025). A novel ALU using distributed arithmetic for real time signal processing application. Proceedings on Engineering Sciences. https://doi.org/10.24874/PES07.01B.011

37. Prasad, M., Challa, N., & Raju, P. (2025). Air quality prediction using genetic algorithm-based feature selection and machine learning techniques for sustainable environmental management. IOP Conference Series: Earth and Environmental Science, 1529(1), 012001. https://doi.org/10.1088/1755-1315/1529/1/012001

38. Prasad, M., Raja Rao, P. B. V., & Lakshmi, K. A. (2025). BISEARCHINS-driven eco-friendly hybrid rideshare system for sustainable and efficient urban transportation. Proceedings on Engineering Sciences. https://doi.org/10.24874/PES07.03A.025

39. Prasad, M., Ramadevi, S., & Lakshmi, K. A. (2025). A study on fatty liver segmentation and classification as revealed by CT scans. In Intelligent systems and sustainable computing: Proceedings of ICISSC (SIST, Vol. 417). Springer. https://doi.org/10.1007/978-981-97-8355-7_36

40. Raja Rao, P., Swathi, C., & Rapaka, A. (2025). Autonomous load balancing of optimized path selection for wireless mesh network. In Proceedings of AMATHE 2025. IEEE. https://doi.org/10.1109/AMATHE65477.2025.11081198

41. Raju, P. J. R. S., Sree, P. K., & Murty, P. T. S. (2025). A novel approach for watermarking medical images using electronic patient record data and a multi-bit-quantisation modulation method. International Journal of Intelligent Engineering Informatics. https://doi.org/10.1504/IJIEI.2025.146687

42. Ramkumar, B. V., Savitha, S., & Kirubanand, V. B. (2025). Adaptive fuzzy heuristic algorithm for dynamic data mining in IoT integrated big data environments. Journal of Fuzzy Extension and Applications. https://doi.org/10.22105/JFEA.2024.484955.1676

43. Rebecca, B., Sandhya, A., & Krishna, B. M. (2025). Marine life ecosystem analysis based on climate change detection using deep learning algorithms. Remote Sensing in Earth Systems Sciences. https://doi.org/10.1007/S41976-025-00212-9

44. Revathy, G., Pokkuluri, K. S., & Gokulraj, S. (2025). Electric vehicle energy management using fuzzy logics and machine learning. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-7352-1.CH010

45. Salini, Y., Pokkuluri, K. S., & Joseph, M. (2025). Machine learning-based swarm optimization for residential demand-based electricity. In Sustainable smart homes and buildings with Internet of Things.

46. Shalem Raju, P. J. R., Prasad, M., & Gompa, N. S. (2025). Predictive modeling for job recommendations: Harnessing the power of KNN, SVM, and LR algorithms. In ICT systems and sustainability: Proceedings of ICT4SD (LNNS, Vol. 1159). Springer. https://doi.org/10.1007/978-981-97-8526-1_9

47. Sharmila, K. S., Revathi, S. T., & Sree, P. K. (2025). DDINet: Drug-drug interaction prediction network based on multi-molecular fingerprint features and multi-head attention centered weighted autoencoder. Journal of Bioinformatics and Computational Biology. https://doi.org/10.1142/S0219720025500039

48. Shubha, S., Venu, D., & Saisandeep, B. (2025). Navigating efficiency: Evaluating wireless ad hoc network protocols with NS-3. Sigma Journal of Engineering and Natural Sciences. https://doi.org/10.14744/SIGMA.2025.00079

49. Sivanuja, M., Raju, P. J. R. S., & Sree, P. K. (2025). A novel ensemble-based deep learning framework combining CNN and transfer learning models for enhanced wildfire detection. In Proceedings of ICCRTEE 2025. IEEE. https://doi.org/10.1109/ICCRTEE64519.2025.11052908

50. Sivanuja, M., Raju, P. J. R. S., & Sree, P. K. (2025). Detecting wildfire hazards using convolutional neural networks. In Proceedings of ICCSAI 2025. IEEE. https://doi.org/10.1109/ICCSAI64074.2025.11063995

51. Sivakumar, R., Prasad, K., & Nayak, B. B. (2025). Augmented and virtual reality based human resource management and its impact on organizational sustainability. WSEAS Transactions on Business and Economics. https://doi.org/10.37394/23207.2025.22.86

52. Sivakumar, R., Singh, K., & Mohapatra, M. R. (2025). Urban air quality monitoring system enhanced by IoT for comprehensive deployment, data collection, and environmental impact analysis. WSEAS Transactions on Environment and Development. https://doi.org/10.37394/232015.2025.21.33

53. Sree, P. K., Tejaswi, M., & Raju, P. J. R. S. (2025). Crime detection with variational autoencoders. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 598). Springer. https://doi.org/10.1007/978-3-031-77078-4_8

54. Sree, P. K., Prasad, M., & Babu, G. R. (2025). Auto encoders with cellular automata for anomaly detection. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 598). Springer. https://doi.org/10.1007/978-3-031-77078-4_28

55. Sri, M. J., Rapaka, A., & Sree, P. K. (2025). Misinformation detection in social media using advanced transformer-based models through BERT and XLNet. In Proceedings of ICCMC 2025. IEEE. https://doi.org/10.1109/ICCMC65190.2025.11140944

56. Gupta, S. (2025). Predicting future rainfall with various machine learning models. Journal of Information Systems Engineering & Management, 10(3S). https://doi.org/10.52783/JISEM.V10I3S.354

57. Varma Ch, P., Ramesh Babu, G., & Venkata Ramana, Ch. (2025). High accuracy classification of Parkinson's disease detection using RNN-graph-LSTM. Proceedings on Engineering Sciences. https://doi.org/10.24874/PES07.01B.010

58. Pokkuluri, K. S., Kolikipogu, R., & Mamta. (2025). Construction and simulation of hybrid neural network and LSTM to language process model. In Integrating neurocomputing with artificial intelligence.

59. Pokkuluri, K. S., Usha Devi, N. S. S. S. N., & Khang, A. (2025). Deep learning for threat detection and analysis. In Privacy and security policies in big data. IGI Global. https://doi.org/10.4018/979-8-3693-6371-3.CH002

2024

1. Ajay, A., et al. (2024). Collaborative intelligence for IoT: Decentralized net security and confidentiality. Journal of Intelligent Systems and Internet of Things. https://doi.org/10.54216/JISIOT.130216

2. Alzubi, J. A., et al. (2024). A robust authentication and trust detection with privacy preservation of data for fog computing in VANET using adaptive deep neural network. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3486811

3. Cheng, Y., Vijayaraj, A., & Rateb, R. (2024). Vehicular fog resource allocation approach for VANETs based on deep adaptive reinforcement learning combined with heuristic information. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3455168

4. D'Souza, M., Nimma, D., & Kongala, L. (2024). Multiclass osteoporosis detection: Enhancing accuracy with woodpecker-optimized CNN-XGBoost. International Journal of Advanced Computer Science and Applications, 15(8). https://doi.org/10.14569/IJACSA.2024.0150889

5. Hu, W., Pokkuluri, K. S., & Palanisamy, P. (2024). RSSI-based 3D wireless sensor node localization using hybrid T cell immune and lotus optimization. Computers, Materials and Continua. https://doi.org/10.32604/CMC.2024.055561

6. Jia, J., Kumarasamy, S. S., & Wang, F. (2024). A robust authentication and trust detection with privacy preservation of data for fog computing in VANET using adaptive deep neural network. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3486811

7. Mangalampalli, S. S., Karri, G. R., & Chakrabarti, T. (2024). An energy and temperature aware deep reinforcement learning workflow scheduler in cloud computing. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3488965

8. Menon, S., Addula, S. R., & Soni, A. (2024). Streamlining task planning systems for improved enactment in contemporary computing surroundings. SN Computer Science. https://doi.org/10.1007/S42979-024-03267-5

9. Mohanapriya, D., Chepur, J., & Subbulakshmi, R. (2024). Investigation of medication reviews and the identification of adverse drug reactions using machine learning algorithms. Measurement: Sensors. https://doi.org/10.1016/J.MEASEN.2024.101240

10. Pokkuluri, K. S. (2024). Convolutional neural networks for enhancing clinical decision-making. Biomedical Journal of Scientific & Technical Research. https://doi.org/10.26717/BJSTR.2024.56.008859

11. Pokkuluri, K. S. (2024). Fuzzy horizon: Unveiling the fog of uncertainty with cognitive cartography and fuzzy logic fusion. Communications on Applied Nonlinear Analysis. https://doi.org/10.52783/CANA.V31.1461

12. Pokkuluri, K. S., Chakrabarti, P., & Usha Devi, N. S. S. S. N. (2024). Hybrid cellular automata with CNN for the prediction of secondary structure of protein. In Innovations in data analytics: Selected papers of ICIDA (LNNS, Vol. 1005). Springer. https://doi.org/10.1007/978-981-97-4928-7_24

13. Pokkuluri, K. S., Chakrabarti, P., & Usha Devi, N. S. S. S. N. (2024). Drug recommendations using support vector machine. In Innovations in data analytics: Selected papers of ICIDA (LNNS, Vol. 1005). Springer. https://doi.org/10.1007/978-981-97-4928-7_13

14. Pokkuluri, K. S., & Khang, A. (2024). Deep learning for identification of behavioral changes. In Social, health, and environmental infrastructures for economic growth. IGI Global. https://doi.org/10.4018/979-8-3693-6055-2.CH004

15. Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2024). 3D convolutional neural networks for predicting protein structure for improved drug recommendation. EAI Endorsed Transactions on Pervasive Health and Technology. https://doi.org/10.4108/EETPHT.10.5685

16. Pokkuluri, K. S., Sssn Usha Devi, N., & Ramesh Babu, G. (2024). Detection of vehicle crashes on roads using deep learning. In Proceedings of ICACCT 2024. IEEE. https://doi.org/10.1109/INCACCT61598.2024.10551202

17. Prerna, P., et al. (2024). Bridging the gap between technology and medicine through the revolutionary impact of the healthcare Internet of Things on remote patient monitoring. Journal of Intelligent Systems and Internet of Things. https://doi.org/10.54216/JISIOT.130217

18. Rao, N. R., Pokkuluri, K. S., & Velusamy, S. (2024). Enhancing rainwater harvesting and groundwater recharge efficiency with multi-dimensional LSTM and clonal selection algorithm. Groundwater for Sustainable Development. https://doi.org/10.1016/J.GSD.2024.101167

19. Sharmila, K. S., Revathi, S. T., & Sree, P. K. (2024). A systematic review on drug-to-drug interaction prediction and cryptographic mechanism for secure drug discovery using AI techniques. International Journal on Artificial Intelligence Tools. https://doi.org/10.1142/S0218213024500039

20. Pokkuluri, K. S., Usha Devi, N., & Khang, A. (2024). Quantum precision in medical imaging. In The quantum evolution. CRC Press. https://doi.org/10.1201/9781032642079-12

21. Pokkuluri, K. S., Usha Devi, N., & Khang, A. (2024). Quantum-powered hate speech detection. In The quantum evolution. CRC Press. https://doi.org/10.1201/9781032642079-19

22. Pokkuluri, K. S., Usha Devi, N. S. S. S. N., & Chakrabarti, P. (2024). Protein structure prediction using convolutional neural networks augmented with cellular automata. In Computational intelligence: Theory and applications.

23. Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2024). Enhancing image segmentation accuracy using deep learning techniques. Journal of Advanced Research in Applied Sciences and Engineering Technology, 49(1), 139–148. https://doi.org/10.37934/ARASET.49.1.139148

24. Gantayat, S. S., Pimple, K. M., & Pokkuluri, K. S. (2024). IoMT type-2 fuzzy logic implementation. In Advances in fuzzy-based Internet of Medical Things (IoMT). Wiley. https://doi.org/10.1002/9781394242252.CH12

25. Pokkuluri, K. S., Khang, A., & Usha Devi, N. S. S. S. N. (2024). Long short-term memory networks for automated waste treatment augmented with IoT and bioelectric sensors. In Handbook of research on microbial tools for environmental waste management. IGI Global. https://doi.org/10.4018/979-8-3693-6016-3.CH016

26. Pokkuluri, K. S., Khang, A., & Usha Devi, N. S. S. S. N. (2024). Integration of machine learning augmented with biosensors for enhanced water quality monitoring. In Handbook of research on microbial tools for environmental waste management. IGI Global. https://doi.org/10.4018/979-8-3693-2069-3.CH009

27. Pokkuluri, K. S., Khang, A., & Usha Devi, N. S. S. S. N. (2024). Enhancing aquaculture efficiency. In Handbook of research on microbial tools for environmental waste management. IGI Global. https://doi.org/10.4018/979-8-3693-2069-3.CH022

28. Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2024). CulinarySpectra. In Handbook of research on holistic optimization techniques in the hospitality, tourism, and travel industry. IGI Global. https://doi.org/10.4018/979-8-3693-1814-0.CH003

29. Veera V Rama Rao, M., Pokkuluri, K. S., & Shankar, A. (2024). A secured and energy-efficient system for patient e-healthcare monitoring using the Internet of Medical Things (IoMT). Data & Metadata. https://doi.org/10.56294/DM2024368

30. Murty, P. T. S., Sree, P. K., & Vineetha, D. (2024). Detection and classification of potholes using CNN. In Proceedings of CCICT 2024. IEEE. https://doi.org/10.1109/CCICT62777.2024.00026

31. Prasad, M., Teja, A. L. S., & Pokkuluri, K. S. (2024). Emergency message prioritization and scheduling in vehicular ad hoc networks. In Proceedings of CCICT 2024. IEEE. https://doi.org/10.1109/CCICT62777.2024.00042

32. Chintalapati, P. V., Paluri, S. S., & Sree, P. K. (2024). A research model for automated prediction and analysis of job interview performance. In Proceedings of CCICT 2024. IEEE. https://doi.org/10.1109/CCICT62777.2024.00055

33. Babu, G. R., Chintalapati, P. V., & Kumar, K. S. (2024). An advanced artificial intelligence-driven smart home towards ontology-based energy efficiency management system. In Innovations in data analytics: Selected papers of ICIDA (LNNS, Vol. 972). Springer. https://doi.org/10.1007/978-981-97-3466-5_24

34. Komperla, R. C. A., Pokkuluri, K. S., & Rahila, J. (2024). Revolutionizing biometrics with AI-enhanced X-ray and MRI analysis. In Internet of Things and advanced application in healthcare. IGI Global. https://doi.org/10.4018/979-8-3693-5946-4.CH001

35. Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2024). Designing LSTM networks for emotion modelling. In Identifying, treating, and preventing childhood trauma in rural communities. IGI Global. https://doi.org/10.4018/979-8-3693-1910-9.CH006

36. Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2024). Deep insights. In Advanced pharmacological uses of medicinal plants and natural products. IGI Global. https://doi.org/10.4018/979-8-3693-3218-4.CH012

37. Pokkuluri, K. S., & Usha Devi, N. (2024). Decoding disease. In Advanced pharmacological uses of medicinal plants and natural products. IGI Global. https://doi.org/10.4018/979-8-3693-3218-4.CH010

38. Sree, P. K., Usha Devi, N. S., & Raja Rao, P. (2024). Drug recommendations using a reviews and sentiment analysis by RNN. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 536). Springer. https://doi.org/10.1007/978-3-031-48888-7_11

39. Prasad, M., Lakshmi, K. A., & Das, G. S. (2024). A CNN and TF techniques development for efficient identification of floral recognition. In Proceedings of IC2PCT 2024. IEEE. https://doi.org/10.1109/IC2PCT60090.2024.10486528

40. Pbv, R. R., Prasad, M., & V V Satyanarayana, B. (2024). An efficient cancer detection model using ML and transfer learning techniques. In Proceedings of ICDCOT 2024. IEEE. https://doi.org/10.1109/ICDCOT61034.2024.10515383

41. Pokkuluri, K. S. (2024). Auto encoders with cellular automata for anomaly detection. Journal of Electrical Systems. https://doi.org/10.52783/JES.1131

42. Pokkuluri Kiran Sree. (2024). Convolutional neural networks for enhancing clinical decision-making. Biomedical Journal of Scientific & Technical Research.

43. Raja Rao, P. B. V. (2024). Generic framework for vehicle identification system with deep learning models. Journal of Electrical Systems. https://doi.org/10.52783/JES.1440

44. Veera V Rama Rao, M. (2024). Optimizing breast cancer diagnosis with advanced deep learning techniques in medical imaging. Journal of Electrical Systems. https://doi.org/10.52783/JES.1461

45. Veera V Rama Rao, M. (2024). Enhancing network security: Leveraging machine learning for intrusion detection. Journal of Electrical Systems. https://doi.org/10.52783/JES.1460

46. Prem Kumar, P. S. (2024). 3D convolutional neural networks for video recognition. Communications on Applied Nonlinear Analysis, 32. https://doi.org/10.52783/CANA.V32.2205

47. Shukla, T. D., Nimma, D., & Bala, B. K. (2024). Utilizing artificial intelligence for enhancing performance and preventing injuries in sports analytics. In Proceedings of IC-SIT 2024. IEEE. https://doi.org/10.1109/IC-SIT63503.2024.10862063

48. Pokkuluri, K. S., Nigam, N., & Chhaya. (2024). Efficient novel method for EEG signal classification in epileptic seizure identification using metaheuristic deep learning. In Proceedings of ICRASET 2024. IEEE. https://doi.org/10.1109/ICRASET63057.2024.10895075

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54. Pokkuluri, K. S., Soni, N., & Sharma, D. (2024). Optimized fetal ECG feature extraction with genetic algorithm based heart rate detection. In Proceedings of ICTBIG 2024. IEEE. https://doi.org/10.1109/ICTBIG64922.2024.10911158

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2023

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3. Mangalampalli, S. S., Karri, G. R., & Satish, G. N. (2023). SLA based workflow scheduling algorithm in cloud computing using Harris Hawks optimization. EAI Endorsed Transactions on Scalable Information Systems. https://doi.org/10.4108/EETSIS.4005

4. Pamarthi, N., Satyanarayana Murty, P. T., & Maram, B. (2023). A research study of heart health monitoring using deep learning and IoT. In Proceedings of IDICAIEI 2023. IEEE. https://doi.org/10.1109/IDICAIEI58380.2023.10406326

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6. Pokkuluri, K. S. (2023). Machine learning for quality in health care: A comprehensive review. Biomedical Journal of Scientific & Technical Research. https://doi.org/10.26717/BJSTR.2023.51.008138

7. Pokkuluri, K. S. (2023). Deep learning in bioinformatics—Current advances and future prospects. Biomedical Journal of Scientific & Technical Research.

8. Pokkuluri, K. S., & Usha Devi, N. (2023). Review on healthcare quality using machine learning methods. In Internet of Things and advanced application in healthcare. IGI Global. https://doi.org/10.4018/979-8-3693-0876-9.CH024

9. Pokkuluri, K. S., Prasad, M., & Shalem Raju, P. J. R. (2023). A comprehensive analysis on risk prediction of heart disease using machine learning models. International Journal on Recent and Innovation Trends in Computing and Communication. https://doi.org/10.17762/IJRITCC.V11I11S.8295

10. Prasad, M., Sudha Rani, P. R., & Ramana, C. V. (2023). Blockchain-enabled on-path caching for efficient and reliable content delivery in information-centric networks. International Journal on Recent and Innovation Trends in Computing and Communication. https://doi.org/10.17762/IJRITCC.V11I9.8397

11. Raja Rao, P. B. V., Prasad, M., & Satyanarayana Murty, P. T. (2023). Enhancing the MANET AODV forecast of a broken link with LBP. In Intelligent systems and sustainable computing: Proceedings of ICISSC (SIST, Vol. 363). Springer. https://doi.org/10.1007/978-981-99-4717-1_6

12. Rapaka, A., Mallela, R. B., & Thammuluri, R. (2023). A comprehensive survey of convolutional neural networks for skin cancer classification and prediction. International Journal on Recent and Innovation Trends in Computing and Communication. https://doi.org/10.17762/IJRITCC.V11I11S.8085

13. Sharmila, K. S., Revathi, S. T., & Sree, P. K. (2023). Enhancing drug-drug interaction prediction: A unified similarity-based neural network approach. In Proceedings of GCITC 2023. IEEE. https://doi.org/10.1109/GCITC60406.2023.10425844

14. Sharmila, K. S., Revathi, S. T., & Kiran Sree, P. (2023). Drug-drug interaction: An improved prediction approach based on convolutional neural networks. In Proceedings of ICSCNA 2023. IEEE. https://doi.org/10.1109/ICSCNA58489.2023.10370722

15. Sharmila, K. S., Revathi, S. T., & Pokkuluri, K. S. (2023). Convolution neural networks based lungs disease detection and severity classification. In Proceedings of ICCCI 2023. IEEE. https://doi.org/10.1109/ICCCI56745.2023.10128188

16. Sree, P. K., Chintalapati, P. V., & Raja Rao, P. B. V. (2023). Waste management detection using deep learning. In Proceedings of ICCIT 2023. IEEE. https://doi.org/10.1109/ICCIT58132.2023.10273898

17. Sree, P. K., Babu, G. R., & Prasad, M. (2023). Fake news detection using cellular automata based deep learning. In Proceedings of ICCIT 2023. IEEE. https://doi.org/10.1109/ICCIT58132.2023.10273875

18. Babu, G. R., Varma Chintalapati, P., & Ramana, C. V. (2023). A context sensitive with effective task migration in mobile cloud computing services. In Proceedings of ICCIT 2023. IEEE. https://doi.org/10.1109/ICCIT58132.2023.10273949

19. Chintalapati, P. V., Babu, G. R., & Kumar, G. S. (2023). Usage of AI techniques for cyberthreat security system in Android mobile devices. In Proceedings of ICICC (LNNS, Vol. 703). Springer. https://doi.org/10.1007/978-981-99-3315-0_33

20. Khang, A., Rath, K. C., & Panda, S. K. (2023). Revolutionizing agriculture. In Handbook of research on microbial tools for environmental waste management. IGI Global. https://doi.org/10.4018/978-1-6684-9231-4.CH001

21. Pokkuluri, K. S. (2023). Deep learning for heart attack prediction. Biomedical Journal of Scientific & Technical Research. https://doi.org/10.26717/BJSTR.2023.54.008522

22. Prasad, P. S., Sangeetha, T., & Reddy, V. K. (2023). A novel approach for detecting anomalies in clusters using soft computing techniques. AIP Conference Proceedings. https://doi.org/10.1063/5.0123212

23. Raju, P. J. R. S., Kiran, K. V. D., & Pokkuluri, K. S. (2023). Digital image watermarking based on hybrid FRT-HD-DWT domain and flamingo search optimisation. International Journal of Computational Vision and Robotics. https://doi.org/10.1504/IJCVR.2023.134319

24. Revathy, G., Sree, P. K., & Vadivu, S. S. (2023). Visual learning with dynamic recall. In Soft computing and signal processing: Proceedings of ICSCSP (SIST, Vol. 313). Springer. https://doi.org/10.1007/978-981-19-8669-7_11

25. Satyanarayana Murty, P. T., Prasad, M., & Phaneendra Varma, C. (2023). A hybrid intelligent cryptography algorithm for distributed big data storage in cloud computing security. In Multi-disciplinary trends in AI: MIWAI (LNAI, Vol. 14078). Springer. https://doi.org/10.1007/978-3-031-36402-0_59

26. Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2023). Employee attrition prediction using KNN machine learning algorithm. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.4452350

2022

1. Behdenna, S., Belalem, G., & Barigou, F. (2022). An ontology-based approach to enhance explicit aspect extraction in standard Arabic reviews. International Journal of Computing and Digital Systems. https://doi.org/10.12785/IJCDS/110123

2. Mangalampalli, S., Pokkuluri, K. S., & Mangalampalli, V. K. (2022). Energy efficient VM consolidation technique in cloud computing using cat swarm optimization. In Machine intelligence and data science applications: MIDAS (LNDECT, Vol. 132). Springer. https://doi.org/10.1007/978-981-19-2347-0_36

3. Mangalampalli, S., & Pokkuluri, K. S. (2022). Effective VM placement mechanism in cloud computing using cuckoo search optimization. In Proceedings of IC3P 2022. IEEE. https://doi.org/10.1109/IC3P52835.2022.00057

4. Mangalampalli, S., & Sree, P. K. (2022). An effective VM consolidation mechanism by using the hybridization of PSO and cuckoo search algorithms. In Computational intelligence in data mining: ICCIDM (SIST, Vol. 281). Springer. https://doi.org/10.1007/978-981-16-9447-9_37

5. Mangalampalli, S., & Pokkuluri, K. S. (2022). An effective workflow scheduling algorithm in cloud computing using cat swarm optimization. ECS Transactions. https://doi.org/10.1149/10701.2523ECST

6. Mangalampalli, S., & Pokkuluri, K. S. (2022). An efficient workflow scheduling algorithm in cloud computing using cuckoo search and PSO algorithms. In Innovations in computer science and engineering: ICICSE (LNNS, Vol. 385). Springer. https://doi.org/10.1007/978-981-16-8987-1_15

7. Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2022). Crop disease prediction with convolution neural network (CNN) augmented with cellular automata. International Arab Journal of Information Technology, 19(5). https://doi.org/10.34028/IAJIT/19/5/8

8. Pokkuluri, K. S., Usha Devi, N. S. S. S. N., & Mangalampalli, S. (2022). DLCP: A robust deep learning with non-linear CA mechanism for lung cancer prediction. In Innovations in computer science and engineering: ICICSE (LNNS, Vol. 385). Springer. https://doi.org/10.1007/978-981-16-8987-1_31

9. Pokkuluri, K. S., Usha Devi, N. S. S. S. N., & Mangalampalli, S. (2022). DLHAP: A novel deep learning with hybrid CA mechanism for heart attack prediction. In Innovations in computer science and engineering: ICICSE (LNNS, Vol. 385). Springer. https://doi.org/10.1007/978-981-16-8987-1_32

10. Ramesh Babu, G., Phaneendra Varma, Ch., & Kumar, G. S. C. (2022). A declarative systematic approach to machine learning. In Proceedings of SSTEPS 2022. IEEE. https://doi.org/10.1109/SSTEPS57475.2022.00034

11. Varma, C. P., Babu, G. R., & Sai, N. R. (2022). Usage of classifier ensemble for security enrichment in IDS. In Proceedings of ICACRS 2022. IEEE. https://doi.org/10.1109/ICACRS55517.2022.10029251

12. Pokkuluri, K. S., Shalem Raju, P. J. R., & Kasula, K. V. D. (2022). Digital image watermarking based on hybrid FRT-HD-DWT domain and flamingo search optimisation. International Journal of Computational Vision and Robotics. https://doi.org/10.1504/IJCVR.2022.10050520

13. Prasad, M., Raja Rao, P. B. V., & Ramana, M. C. V. (2022). Fog-based data analytics scheme using edge affinity-based management. NeuroQuantology.

2021

1. Mangalampalli, S., Sree, P. K., & Kocherla, R. T. (2021). Prioritized load balancer for minimization of VM and data transfer cost in cloud computing.

2. Pokkuluri, K. S. (2021). DLCDI: A novel deep learning mechanism for chronic diseases identification.

3. Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2021). A secure cellular automata integrated deep learning mechanism for health informatics. International Arab Journal of Information Technology. https://doi.org/10.34028/IAJIT/18/6/5

2020

1. Kiran, K. U., Shakeela, S., & Pavan Kalyan, G. S. R. (2020). Framework for environment quality monitoring using radial support vector regression. Journal of Computational and Theoretical Nanoscience. https://doi.org/10.1166/JCTN.2020.8866

2. Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2020). COVID-19 hotspot trend prediction using hybrid cellular automata in India. Engineering Science & Technology. https://doi.org/10.37256/EST.212021610

3. Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2020). A novel cellular automata classifier for COVID-19 prediction. Journal of Health Sciences. https://doi.org/10.17532/JHSCI.2020.907

4. Pokkuluri, K. S., Usha Devi, N. S. S. S. N., et al. (2020). Deep convolution network for COVID-19 death rate prediction. i-manager's Journal on Information Technology, 9(1). https://doi.org/10.26634/JIT.9.1.17254

5. Mohamed Iqbal, M., Chandra Kiran, P., & Shakthivel, R. (2020). LabVIEW-based virtual laboratories for electrical engineering education with real-time implementation. In Proceedings of ICSCSP 2020. Springer. https://doi.org/10.1007/978-981-15-2475-2_49

2019

1. Pokkuluri, K. S. (2019, December). Deep learning mechanism augmented with 16-hybrid cellular automata for secondary structure prediction. International Journal of Innovative Technology and Exploring Engineering. https://doi.org/10.35940/IJITEE.B6458.129219

2. Pokkuluri, K. S. (2019, December). Gold price prediction using eight neighborhood non linear cellular automata. International Journal of Innovative Technology and Exploring Engineering. https://doi.org/10.35940/IJITEE.B7727.129219

3. Mishra, A. (2019). An artificial intelligence based approach to determine the elongation% and ultimate tensile strength of friction stir welded dissimilar marine grade aluminium alloy joints.

2018

1. Reddy, Ch. S., Sagar, B., & Reddy, S. S. (2018). The structural design of the multistorey building.

2. Kiran, V., Kumar, N., & Reddy, V. (2018). Paediatric femoral neck fractures: Our 5 years of experience. International Journal of Orthopaedics.

3. Simulation analysis on network layer attacks in wireless mesh networks. (2018). International Journal of Engineering and Technology.

2017

1. Mangalampalli, S., Reedy, K. G., & Raju, V. P. (2017). An effective analysis on various scheduling algorithms in cloud computing. In Proceedings of ICICI 2017. IEEE. https://doi.org/10.1109/ICICI.2017.8365274

2. Mohan, R., & Sree, P. K. (2017). An extensive survey on deep learning applications.

3. Sree, P. K., Rao, P. S. V. S., & Devi, S. S. S. N. U. N. (2017). CDLGP: A novel unsupervised classifier using deep learning for gene prediction. In Proceedings of ICPCSI 2017. IEEE. https://doi.org/10.1109/ICPCSI.2017.8392232

4. Sree, P. K., Devi, S. S. S. N. U. N., & Sudheer, M. S. (2017). A robust deep learning mechanism augmented with cellular automata for DNA computing. In Proceedings of ICPCSI 2017. IEEE. https://doi.org/10.1109/ICPCSI.2017.8391921

2016

1. Resource allocation arbitrarily to large number of clients within the cloud. (2016). International Journal of Reviews on Recent Electronics and Computer Science.

2015

1. Pokkuluri, K. S., & Devi, S. S. S. N. U. N. (2015). RTWPCAMARM: A dynamic real time weather prediction system with 8 neighborhood hybrid cellular automata and modified association rule mining. In Proceedings of ICACCI 2015. IEEE. https://doi.org/10.1109/ICACCI.2015.7275609

2. Kiran, P., & Ramesh, I. (2015). Babu. Investigating cellular automata based network intrusion detection system for fixed networks (NIDWCA).

3. Aboshosha, A., Pokkuluri, K. S., & Solaiman, B. (2015). GVIP-Volume 8-Issue 2. https://doi.org/10.13140/RG.2.1.4990.4083

2014

1. Pokkuluri, K. S., Babu, I. R., & Nedunuri, S. S. S. N. U. D. (2014). IN-MACA-MCC: Integrated multiple attractor cellular automata with modified clonal classifier for human protein coding and promoter prediction. Advances in Bioinformatics. https://doi.org/10.1155/2014/261362

2. Pokkuluri, K. S. (2014). Cellular automata in splice site prediction. MOJ Proteomics & Bioinformatics. https://doi.org/10.15406/MOJPB.2014.01.00013

3. Pokkuluri, K. S., Babu, I. R., & Usha Devi, N. (2014). A fast multiple attractor cellular automata with modified clonal classifier for coding region prediction in human genome. Journal of Bioinformatics and Intelligent Control. https://doi.org/10.1166/JBIC.2014.1077

4. Pokkuluri, K. S., Babu, I. R., & Usha Devi, N. (2014). A fast multiple attractor cellular automata with modified clonal classifier promoter region prediction in eukaryotes. Journal of Bioinformatics and Intelligent Control. https://doi.org/10.1166/JBIC.2014.1075

5. Pokkuluri, K. S., & Babu, I. R. (2014). AIX-MACA-Y multiple attractor cellular automata based clonal classifier for promoter and protein coding region prediction. Journal of Bioinformatics and Intelligent Control. https://doi.org/10.1166/JBIC.2014.1071

6. Pokkuluri, K. S., Babu, I. R., & Nedunuri, S. S. S. N. U. D. (2014). PRMACA: A promoter region identification using multiple attractor cellular automata (MACA). In Advances in intelligent systems and computing. Springer. https://doi.org/10.1007/978-3-319-03107-1_42

7. Srinivasu, N., Samdani, S. M., & Kiran, L. S. (2014). Asynchronous data access and transaction decomposition in distributed databases. International Journal of Advanced Research in Computer Science.

8. Kiran Sree, P., Babu, I. R., & Usha Devi, N. S. S. S. N. (2014). AIS-MACA-Z: MACA based clonal classifier for splicing site, protein coding and promoter region identification in eukaryotes. ArXiv.

9. Pokkuluri, K. S., & Babu, I. R. (2014). A human promoter prediction using MACA-CLONAL classifier.

10. Pokkuluri, K. S., Babu, I. R., & Usha Devi, N. S. S. S. N. (2014, January). Towards a cellular automata based network intrusion detection system with power level metric in wireless adhoc networks [Preprint]. https://pprn:22248379

11. Babu, I. R., & Pokkuluri, K. S. (2014, January). Improving quality of clustering using cellular automata for information retrieval [Preprint]. https://doi.org/10.3844/JCSSP.2008.167.171

12. Babu, I. R., & Pokkuluri, K. S. (2014, May). Clonal-based cellular automata in bioinformatics [Preprint].

13. Babu, I. R., Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2014, January). HMACA: Towards proposing a cellular automata based tool for protein coding, promoter region identification and protein structure prediction [Preprint].

14. Babu, I. R., & Pokkuluri, K. S. (2014, March). AIS-INMACA: A novel integrated MACA based clonal classifier for protein coding and promoter region prediction [Preprint]. https://doi.org/10.17303/JBCG.2014.1.103

15. Babu, I. R., & Pokkuluri, K. S. (2014, March). An extensive report on the efficiency of AIS-INMACA [Preprint].

16. Babu, I. R., Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2014, April). Cellular automata and its applications in bioinformatics: A review [Preprint].

17. Babu, I. R., Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2014, April). A fast multiple attractor cellular automata with modified clonal classifier for splicing site prediction in human genome [Preprint].

18. Babu, I. R., Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2014, April). AIS-MACA-Z: MACA based clonal classifier for splicing site, protein coding and promoter region identification in eukaryotes [Preprint].

19. Babu, I. R., Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2014, January). PSMACA: An automated protein structure prediction using MACA [Preprint].

2013

1. Sree, P. K. (2013). An enhanced SLA based framework for bulk provisioning in telecommunication network. International Journal of Advanced Research in Computer and Communication Engineering.

2. Sree, P. K. (2013). HMACA: Towards proposing cellular automata based tool for protein coding, promoter region identification and protein structure prediction. International Journal of Research in Computer Applications & Information Technology.

3. Pokkuluri, K. S., Babu, I. R., & Usha Devi, N. S. S. S. N. (2013). AIS-PRMACA: Artificial immune system based multiple attractor cellular automata for strengthening PRMACA, promoter region identification. SIJ Transactions on Computer Science Engineering & Its Applications. https://doi.org/10.9756/SIJCSEA/V1I4/0104530101

4. Pokkuluri, K. S., Babu, I. R., & Usha Devi, N. S. S. S. N. (2013). AIS-PSMACA: Towards proposing an artificial immune system for strengthening PSMACA: An automated protein structure prediction using multiple attractor cellular automata. Global Journal of Computer Science and Technology.

5. Pokkuluri, K. S., Raju, G. V. S., & Usha Devi, N. S. S. S. N. (2013). Cellular automata based feedback mechanism in strengthening biological sequence analysis approach to robotic soccer. ArXiv.

6. Nanneti, I. N., & Sree, P. K. (2013). A novel approach to automatic age and gender recognition by using neural network system.

7. Sree, P. K., Babu, I. R., & Devi, N. U. (2013, November). FELFCNCA: Fast & efficient log file compression using non linear cellular automata classifier [Preprint].

8. Kiran Sree, P., Ramesh Babu, I., & Usha Devi, N. S. S. S. N. (2013, October). Multiple attractor cellular automata (MACA) for addressing major problems in bioinformatics [Preprint].

9. Sree, P. K., & Ramesh Babu, I. (2013, December). Face detection from still and video images using unsupervised cellular automata with K means clustering algorithm [Preprint].

10. Babu, I. R., & Pokkuluri, K. S. (2013, December). Power-aware hybrid intrusion detection system (PHIDS) using cellular automata in wireless AdHoc networks [Preprint].

11. Babu, I. R., Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2013, October). An extensive report on cellular automata based artificial immune system for strengthening automated protein prediction [Preprint].

2010

1. Sree, K., & Babu, R. (2010). Identification of promoter region in genomic DNA using cellular automata based text clustering. International Arab Journal of Information Technology.

2009

1. Sree, P. K., Babu, I. R., & Devi, N. S. S. S. N. U. (2009). Cellular automata with biological sequence analysis approach to robotic soccer. International Journal of Computer Science and Applications.

2. Kiran Sree, P., & Babu, I. R. (2009). Investigating an artificial immune system to strengthen the promoter region identification and promoter coding region identification using cellular automata classifier. International Journal of Bioinformatics Research and Applications.

3. Sree, P. K., Babu, I. R., & Usha Devi, N. S. S. S. N. (2009). Investigating an artificial immune system to strengthen protein structure prediction and protein coding region identification using the cellular automata classifier. International Journal of Bioinformatics Research and Applications. https://doi.org/10.1504/IJBRA.2009.029044

2008

1. Sree, P. K., & Babu, I. R. (2008). Towards a cellular automata based network intrusion detection system with power level metric in wireless adhoc networks (IDFADNWCA). In Proceedings of ICACTE 2008. IEEE. https://doi.org/10.1109/ICACTE.2008.160

2. Sree, P. K., & Babu, I. R. (2008). Investigating cellular automata based network intrusion detection system for fixed networks (NIDWCA). In Proceedings of ICACTE 2008. IEEE. https://doi.org/10.1109/ICACTE.2008.159

3. Sree, K. P., Babu, R. I., & Devi, U. N. S. S. N. (2008). NTCA: A novel text clustering algorithm built on cellular automata based local search and K-means algorithm for identifying the protein coding regions in genomic DNA. Research Journal of Biotechnology.

4. Sree, P. K. (2008). Exploring a novel approach for providing software security using soft computing systems. International Journal of Security and Its Applications.

5. Sree, P. K., & Babu, I. R. (2008). Identification of protein coding regions in genomic DNA using unsupervised FMACA based pattern classifier. International Journal of Computer Science and Network Security.

6. Sree, P. K., Babu, I. R., & Devi, N. S. S. S. N. U. (2008). BSRCA: Biological sequence analysis approach to robotic soccer with cellular automata classifier. In KMICE 2008 - Knowledge Management International Conference.

7. Sree, P. K., Babu, I. R., & Devi, N. S. S. S. N. U. (2008). Power-aware hybrid intrusion detection system (PHIDS) using cellular automata in wireless ad hoc networks. WSEAS Transactions on Computers.

8. Sree, P. K., Babu, I. R., & Devi, N. S. S. S. N. U. (2008). Power-aware hybrid intrusion detection system using support vector machine in wireless ad hoc networks. In KMICE 2008 - Knowledge Management International Conference.

9. Sree, P. K. (2008). An efficient parallel IP lookup technique for IPv6 routers using multiple hashing with ternary marker storage with cellular automata and control prefix expansion. In KMICE 2008 - Knowledge Management International Conference.

10. Sree, P. K., Babu, I. R., & Devi, N. S. S. S. N. U. (2008). A novel protein coding region identifying tool using cellular automata classifier with trust-region method and parallel scan algorithm (NPCRITCACA). International Journal of Biotechnology & Biochemistry.

11. Sree, P. K. (2008). NPCRIT: A novel protein coding region identifying tool using decision tree classifier with trust-region method & parallel scan algorithm. International Journal of Biotechnology & Biochemistry.

12. Sree, P. K., Raju, G., & Devi, N. S. S. S. N. U. (2008). NTCA: A novel text clustering algorithm built on cellular automata based local search and K-means algorithm for identifying the protein coding regions in genomic DNA.

13. Sree, P. K. (2008). An efficient parallel IP lookup technique for IPv6 routers using multiple hashing with ternary marker storage. African Journal of Information & Communication Technology. https://doi.org/10.5130/AJICT.V6I1.627

Important Bioinformatics Research Articles

1. Investigating an Artificial Immune System to Strengthen the Protein Structure Prediction and Protein Coding Region Identification using Cellular Automata Classifier. International Journal of Bioinformatics Research and Applications ,Vol 5,Number 6,pp 647-662, ISSN : 1744-5493. (2009) (Inderscience Journals , UK )Listed & Recognized in US National Library of Medicine National Institutes of Health .National Center for Biotechnology Information(Government of USA)PMID: 19887338 [PubMed - indexed for MEDLINE]   H Index (Citation Index): 08 (SCImago, www.scimagojr.com)   (Nine Years Old Journal)
2. Identification of Promoter Region in Genomic DNA Using Cellular Automata Based Text  Clustering. The International Arab Journal of Information Technology (IAJIT),Volume 7,No 1,2010,pp 75-78. ISSN:1683-3198H Index (Citation Index): 05 (SCImago, www.scimagojr.com)(Eleven Years Old Journal)( SCI Indexed Journal)
3. A Fast Multiple Attractor Cellular Automata with Modified Clonal Classifier for Coding Region Prediction in Human Genome, Journal of Bioinformatics and Intelligent Control, Vol. 3,  2014, pp 1-6. DOI:10.1166/jbic.2014.1077        (American Scientific Publications, USA)
4. A Fast Multiple Attractor Cellular Automata with Modified Clonal Classifier Promoter Region Prediction in Eukaryotes.Journal of Bioinformatics and Intelligent Control, Vol. 3, 1–6, 2014. DOI:10.1166/jbic.2014.1077 (American Scientific Publications, USA)
5. 5.MACA-MCC-DA: A Fast MACA with Modified Clonal Classifier Promoter Region Prediction in Drosophila and Arabidopsis. European Journal of Biotechnology and Bioscience, 1 (6), 2014, pp 22-26, Impact Factor: 1.74 
6. Cellular Automata in Splice Site Prediction. European Journal of Biotechnology and Bioscience, 1 (6), 2014, pp 36-39, Impact Factor: 1.74 
7. AIX-MACA-Y Multiple Attractor Cellular Automata Based Clonal Classifier for Promoter and Protein Coding Region Prediction. Journal of Bioinformatics and Intelligent Control 3, no. 1 (2014): 23-30. DOI:10.1166/jbic.2014.1071, (American Scientific Publications, USA)
8. PSMACA: An Automated Protein Structure Prediction Using MACA (Multiple Attractor Cellular Automata). Journal of Bioinformatics and Intelligent Control 2, no. 3 (2013): 211-215. DOI:10.1166/jbic.2013.1052 (American Scientific Publications, USA) 
9. An extensive report on Cellular Automata based Artificial Immune System for strengthening Automated Protein Prediction. Advances in Biomedical Engineering Research (ABER) Volume 1 Issue 3, September 2013, pp 45-51. Science Publications (USA). 
10. A Novel Protein Coding Region Identifying Tool using Cellular Automata Classifier with Trust-Region Method and Parallel Scan Algorithm (NPCRITCACA). International Journal of Biotechnology & Biochemistry (IJBB) Volume 4, 177-189 Number 2 (December 2008).(Eight Years Old Journal)  Listed in Indian Science Abstracts, ISSN: 0019-6339,Volume  45, Number 22, November 2009.
11. HMACA: Towards proposing Cellular Automata based tool for protein coding, promoter region identification and protein structure prediction. International Journal of Research in Computer Applications & Information Technology, Volume 1 Number 1, pp 26-31,2013.
12. PRMACA: A Promoter Region identification using Multiple Attractor Cellular Automata (MACA) in the proceedings CT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol I Advances in Intelligent Systems and Computing Volume 248, 2014, pp 393-399(Springer-AISC series)
13. Towards Proposing an Artificial Immune System for strengthening PSMACA: An Automated Protein Structure Prediction using Multiple Attractor Cellular Automata proceedings of International Conference on Advances in electrical, electronics, mechanical and Computer Science(ICAEEMCS)-2013, ISBN: 978-93-81693-66-04 on September 2^nd 2013, Hyderabad.
14. Multiple Attractor Cellular Automata (MACA) for Addressing Major Problems in Bioinformatics in Review of Bioinformatics and Biometrics (RBB) Volume 2 Issue 3, September 2013, pp70-76.
15. Protein coding region Identification ,in  proceedings of 2^nd    International Conference on Proteomics Bioinformatics, July 2-4, 2012 Embassy Suites Las Vegas, USA “,( Special Issue of Journal of Proteomics & Bioinformatics. (USA), Volume 5 Issue 6 – 123, ISSN:0974-276X,H Index (Citation Index): 06 (SCImago, www.scimagojr.com)Impact Factor: 2.2,(Five Years Old Journal) 
16. Hybrid Attractor Cellular Automata for Addressing Major Problems in Bioinformatics in Research and Reviews: Journal of Engineering and Technology, Volume 2 Issue 4, October-2013,pp 42-48.
17. AIS-PRMACA: Artificial Immune System based Multiple Attractor Cellular Automata for Strengthening PRMACA, Promoter Region Identification in The SIJ Transactions on Computer Science Engineering  its Applications (CSEA), The Standard International Journals (The SIJ), Vol. 1, No. 4, Pp. 124-127.(2013)   
18. A novel AIS-MACAX classifier in bioinformatics” in 5th World Congress on Biotechnology, June 25-27, 2014 Valencia Conference Centre, Valencia, Spain.http://dx.doi.org/10.4172/2155-952X.S1.029
19. A Complete Analysis on Modified Clonal Classifier with  MACA for Addressing Various Problems in Bioinformatics in , International Journal of Modern Computer Science (IJMCS), Volume 2, Issue 5, October, 2014
20. IN-AIS-MACA: Integrated Artificial Immune System based Multiple Attractor Cellular Automata for Human Protein Coding and Promoter Prediction of 252bp Length DNA Sequence in Global Journal of Computer Science and Technology, Volume XIV, Issue II, pp 1-9, 2014, USA

21. RTWPCAMARM: A Dynamic Real Time weather prediction system with 8 neighborhood hybrid cellular automata and modified association rule mining,2015 International conference on advances in computing, communications and informatics (icacci), IEEE conference.

 

Important Research Articles

1. Power-Aware Hybrid Intrusion Detection System (PHIDS) using Cellular Automata in Wireless Ad Hoc Networks, in World Scientific and Engineering Academy and Society TRANSACTIONS on COMPUTERS,USA, PP.1848-1874, Issue 11,Volume 7, December, 2008,  ISSN: 1109-2750,  Acceptance Rate: 5.76%,  H Index(Citation Index): 10 (SCImago, www.scimagojr.com),  (Ten Years Old Journal)
2. Improving Quality of Clustering using Cellular Automata for Information retrieval in International Journal of Computer Science 4 (2), 167-171, December, 2008. ISSN 1549-3636. ( Science Publications-USA) ,   H Index (Citation Index): 11(SCImago, www.scimagojr.com),Impact Factor: 1.35  (Nine Years Old Journal)
   DOI : 10.3844/jcssp.2008.167.171
3. Face Detection from still and Video Images using Unsupervised Cellular Automata with K means clustering algorithm in ICGST International Journal on Graphics, Vision and Image Processing (GVIP), ISSN: 1687-398X, Volume 8, Issue II, 2008, (1-7).    (Ten Years Old Journal),  H Index (Citation Index): 05 (SCImago, www.scimagojr.com),  (Six Years Old Journal)
4. Achieving Efficient File Compression with Linear Cellular Automata Pattern Classifier in International Journal of Hybrid Information Technology, pp 15-27,Vol. 6, No. 2, March 2013. ISSN: 1738-9968,(6 Years Old Journal)
5. Non Linear Cellular Automata in Predicting Heart Attack “ International Journal of Hybrid Information Technology, pp 33-40, Vol. 4, No. 1, January, 2011. ISSN: 1738-9968, (6 Years Old Journal)
6. FELFCNCA: Fast & Efficient Log File Compression Using Non Cellular Automata Classifier in International  Journal on Communications (IJC),Volume 1 Issue 1,  December  2012.Science Publications (USA).  . ISSN: 2327-1035
7. CAVDM: Cellular Automata Based Video Cloud Mining Framework for Information Retrieval in Journal of Parallel and Cloud Computing Research (PCCR), pp 1-5, 2013, Vol.1 No.1 April 2013. Science Publications (USA). 
8. Investigating a Cellular Automaton Based Network Intrusion Detection System in fixed networks ” in  2008 International Conference on Advanced Computer Theory and Engineering (ICACTE 2008), 20 - 22, December 2008, Phuket, Thailand.( IEEE Computer Society  Conference)
9. Towards a Cellular Automata Based Network Intrusion Detection System with Power Level Metric in Wireless Adhoc Networks ” in  2008 International Conference on Advanced Computer Theory and Engineering (ICACTE 2008), 20 - 22, December 2008, Phuket, Thailand.( IEEE Computer Society  Conference)
10. Towards an Artificial Immune System to Strengthen Edge Detection and Feature Extraction in Face Recognition Using Cellular Automata”, in, The Second International Conference on Information Processing pp 653-661 ISBN: 978-081-906942-7,ICIP 2008.Banglore, India.(IK International Publishers)

Research Articles

1. Exploring a Novel Approach for providing Software Security Using Soft Computing Systems, International Journal of Security and Its Applications, ISSN: 1738-9976, Vol. 2, No. 2, 51-58, April, 2008. 
2. Improving Quality of Clustering Using Cellular Automata for GIF Image Search, GITAM Journal of Information Communication Technology, Volume 1, July 2008,No 1,88-92.
3. Non Linear Cellular Automata for Achieving Anonymity and Traceability in Wireless Mesh Network Using Ticket Based Security Architecture”, in International Journal of Engineering & Technology, ISSN: 2278-0181, Vol.1 Issue 9, November -2012. 
4. NIDTFM: A Novel Intrusion Detection Technique for MANET Using Elliptic Curve Encryption in Third Innovative Conference on Embedded Systems, Mobile Communication and Computing, 11th- 14th August, 2008, Infosys, Mysore, India.( Macmillan Advanced Research Series Book ISBN: 023-063-618-7)
5. Identification of Protein Coding Regions in Genomic DNA Using Unsupervised FMACA Based Pattern Classifier in International Journal of Computer Science & Network Security with ISSN: 1738-7906, Vol.8, No.1, 305-308. 
6. Towards an Artificial Immune System to Strengthen Edge Detection and Feature Extraction in Face Recognition Using Cellular Automata, in, The Second International Conference on Information Processing (ICIP 2008) ISBN: 8190694247.Banglore, India.    
7. TCAAT: Ticket Based Security Architecture Strengthened with Cellular Automata for Achieving Anonymity and Traceability in wireless Mesh Network , in International Journal of Engineering & Technology, ISSN : 2278-0181, Vol.1 Issue 5, July -2012.       
8. Language independent web data extraction using vision based page segmentation algorithm, International Journal of Research in Engineering and Technology, Vol-02 Iss-04, Apr-2013, pp 635 - 639. 
9. An Efficient Parallel IP Lookup Technique for IPv6 Routers Using Multiple Hashing with  Ternary marker storage, African J. of Inf. & Communications. Technology 6(1): (2011), ISSN 1449-2679.
10. Video data mining framework for information retrieval, in National Conference on Research Prospects in Knowledge Mining (NCKM-2008) pp 107-111, Annamali University.
11. Face Detection from still and Video Images using Cellular Automata Based Decision Tree Classifier with Trust-Region Method & Parallel Scan Algorithm , in 11 the 3IA  International conference on Computer Graphics and Artificial Intelligence(3IA'2008) May 2008, Athens (GREECE).
12. Non linear cellular automata in improving the quality of clustering for medical image processing. Karpagam J Comput Sci 2008, 2(6), 795-803.
13. Cellular Automata with Biological Sequence Analysis Approach to Robotic Soccer. International Journal Of Computer Science And Applications Vol. 2, No. 2, November / December 2009,PP127-134,    ISSN: 0974-1003 .H Index (Citation Index): 05 (SCImago, www.scimagojr.com),(Six Years Old Journal)
14. Power-Aware Hybrid Intrusion Detection System Using Support Vector Machine in Wireless Ad Hoc Networks in Knowledge Management International Conference, Langkawi, MALAYSIA Date: JUN 10-12, 2008.
15. Investigating an artificial immune system to strengthen the promoter region structure prediction and promoter region identification using cellular automata classifier. Karpagam J Comp Sci 2008, 2(5), 704-16.
16. TOWARDS PROPOSING A NOVEL THEORETICAL TECHNIQUE FOR TRAFFIC MONITORING OVER FIXED MONITORS in IMPACT: International Journal of Research inEngineering & Technology (IMPACT: IJRET)Vol. 1, Issue 6, Nov 2013, 29-36 
17. AN INTRUSION DETECTION SYSTEM FOR REAL NETWORK TRAFFIC CLASSIFICATION in INTERNATIONAL JOURNAL OF REVIEWS ON RECENT
    ELECTRONICS AND COMPUTER SCIENCE, IJRRECS/October 2013/Volume-1/Issue-6/1514-1524
18. An Enhanced SLA based Framework for Bulk Provisioning in Telecommunication networks in International Journal of Advanced Research in Computer and Communication Engineering,Vol. 2, Issue 10, October 2013,pp 3953-3958
19. OUTLIER DETECTION THROUGH ONLINE OVER SAMPLING CELLUAR AUTOMATA BASED PCA STRENGTHENED WITH CELLULAR AUTOMATA in International Journal of Computer Engineering & Technology (IJCET).Volume:5, Issue: 12, Pages: 257-263.
20. Towards a Hybrid System With Cellular Automata and Data Mining For Forecasting Severe Weather Patterns In 7th INTERNATIONAL CONFERENCE On“Advances in Computer Sciences, Software Solutions, E-Learning, Information & Communication Technology” (ACSEICT– 2015)31st January and 1St February, 2015,Jawaharlal Nehru University, New Delhi
21. “Cellular Automata Index Based Construction for Shortest Path Computation International Journal of Advanced Technology and Innovative Research Volume.07, IssueNo.18, December-2015, Pages: 3482-3487
22. Identifying User Search Behavior with Effective Segmentation and Encryption,International Journal of Scientific Engineering and Technology Research (IJSETR) i,10440-10444
23. Feature Extraction Mechanism for Dealing with Concept Drifts in Process Mining International Journal of Advanced Technology and Innovative Research Volume.07, IssueNo.20, December-2015, Pages: 3995-3999
24. “Cellular Automata Index Based Construction for Shortest Path Computation" International Journal of Advanced Technology and Innovative Research Volume.07, IssueNo.18, December-2015, Pages: 3482-3487"
25. "Identifying User Search Behavior with Effective Segmentation and Encryption”, International Journal of Scientific Engineering and Technology Research (IJSETR) i,10440-10444.
26. “Ten Dimensional Cellular Automata for Elimination of Aging and Disease” in Global Journal of Computational Intelligence Research

Small Intuition Articles  on Deep Learning

1.     Deep Learning: The future of IT in International Journal of Engineering Research and Technology, ISSN-2278-0181, 2016
   2.   An Extensive Survey on Deep Learning Applications in International Conference on Innovative Research in Engineering, Science, Management and Humanities (ICIRESMH-2017) at (IETE) Institution of Electronics and Telecommunication Engineers, Lodhi Road, Delhi, India on 19th February 2017 ISBN: 978-81-932712-5-4
   3.  Private Auditing with Crypto Data in Public Cloud in International Journal of Scientific Engineering and Technology research, ISSN 2319-8885 Vol.05,Issue.40 November-2016, Pages:8374-8380
   4.    RESOURCE ALLOCATION ARBITRARILY TO LARGE NUMBER OF CLIENTS WITHIN THE CLOUD in INTERNATIONAL JOURNAL OF REVIEWS ON RECENT ELECTRONICS AND COMPUTER SCIENCE, IJRRECS/October 2016/Volume-4/Issue-10/6522-6528 ISSN 2321-5461
   5.   NON UNIFORM ADDITIVE NON UNIFORM CELLULAR AUTOMATA WITH DEEP LEARNING (ACADL)FOR PATTERN CLASSIFICATION in  International Journal of Recent Development in Computer Technology & Software Applications Vol. 2, Issue 2 – 2016(9-11)
   6.   HYBRID CLONAL ALGORITHM USING HYBRID DEEP LEARNING AUGMENTED  WITH CA, International Journal of Recent Development in Computer Technology & Software Applications Vol. 2, Issue 2 – 2016(6-9)
   7.      Deep Learning in Bioinfrmatics Applications in J. Adv. Res. Comp. Tech. Soft. Appl. 2016; 3(3&4)(1-3)
   8.     Additive Cellular Automata Augmented with Deep Learning for Pattern Reorganization J. Adv. Res. Comp. Tech. Soft. Appl. 2016; 3(1&2)(1-3)
   9.   Modified Clonal Algorithm using Deep Learning in J. Adv. Res. Comp. Tech. Soft. Appl. 2016; 3(1&2)(1-3)
   10.  Twenty Dimensional Hybrid Cellular Automata for Elimination of Aging, J. Adv. Res. Comp. Tech. Soft. Appl. 2016; 3(1&2)(1-3)
   11. ARTIFICIAL IMMUNE ARTIFICIAL DEEP LEARNING IN IMAGEPROCESSING & BIOMETRIC APPLICATIONS, in International Journal of Recent Development in Computer Technology & Software Applications Vol. 2, Issue 2 – 2016
   12.A NOVEL AND RELIABLE PROMOTER, PROTEIN CODING AND PROTEIN STRUCTURE PREDICTION USING ARTIFICIAL IMMUNE SYSTEM BASED 116-NEIGHBORHOOD HYBRID CELLULAR AUTOMATA in International Journal of Recent Development in Computer Technology & Software Applications Vol. 2, Issue 2 – 201

2. Awards

• Received the Rashtriya Ratan Award – Certificate of Excellence in 2010 for outstanding achievements and promoting India–International cooperation.
• Honored with the Best Regius Professor of the Year (AI & BI) award in 2022 by Raja Ratna Group for excellence in teaching.
• Received the ITAP 2022 Award for implementing outstanding teaching techniques under the Ideal Teaching Awards Programme.
• Awarded the Aishwarya Memorial Research Excellence Award in 2023 by SERF India for remarkable research contributions in engineering.
• Honored with the Jyestha Acharya Award of Recognition during 2023–24 for significant contributions in education and research.
• Received the Veteran Scholar of Excellence Award in 2024 from AIMER Society for excellence as a faculty member in AI and Engineering.
• Honored with the Bharat Education Excellence Award (BEEA 2K24) in 2024 for excellence in academics and education.
• Received the Deep Learning – Technology Visionary Award in 2024 for contributions in deep learning and technological advancements.
• Awarded the Dr. APJ Abdul Kalam National Pratibha Award in 2025 for contributions in literature, education, and social service.
• Honored with the Best Teacher Award in 2025 by SERF India for excellence in teaching at SVECW.
• Received the Global Supervisor Award in 2026 from SERF India for excellence in academic and research supervision.

Publications

    Publications List

APA 7th Edition

Table 1: Journal Articles

S.No	APA Citation
1	Sree, P. K., & Babu, I. R. (2008). Identification of protein coding regions in genomic DNA using unsupervised FMACA based pattern classifier. International Journal of Computer Science and Network Security.
2	Sree, P. K., Babu, I. R., & Devi, N. S. S. S. N. U. (2008). Power-aware hybrid intrusion detection system (PHIDS) using cellular automata in wireless ad hoc networks. WSEAS Transactions on Computers.
3	Sree, P. K., Babu, I. R., & Devi, U. N. S. S. S. N. (2008). NTCA: A novel text clustering algorithm built on cellular automata based local search and K-means algorithm for identifying the protein coding regions in genomic DNA. Research Journal of Biotechnology.
4	Sree, P. K. (2008). Exploring a novel approach for providing software security using soft computing systems. International Journal of Security and Its Applications.
5	Sree, P. K., Babu, I. R., & Devi, N. S. S. S. N. U. (2008). A novel protein coding region identifying tool using cellular automata classifier with trust-region method and parallel scan algorithm (NPCRITCACA). International Journal of Biotechnology & Biochemistry.
6	Sree, P. K. (2008). NPCRIT: A novel protein coding region identifying tool using decision tree classifier with trust-region method & parallel scan algorithm. International Journal of Biotechnology & Biochemistry.
7	Sree, P. K. (2008). An efficient parallel IP lookup technique for IPv6 routers using multiple hashing with ternary marker storage. African Journal of Information & Communication Technology. https://doi.org/10.5130/AJICT.V6I1.627
8	Sree, P. K., Babu, I. R., & Devi, N. S. S. S. N. U. (2009). Cellular automata with biological sequence analysis approach to robotic soccer. International Journal of Computer Science and Applications.
9	Kiran Sree, P., & Babu, I. R. (2009). Investigating an artificial immune system to strengthen the promoter region identification and promoter coding region identification using cellular automata classifier. International Journal of Bioinformatics Research and Applications.
10	Sree, P. K., Babu, I. R., & Usha Devi, N. S. S. S. N. (2009). Investigating an artificial immune system to strengthen protein structure prediction and protein coding region identification using the cellular automata classifier. International Journal of Bioinformatics Research and Applications. https://doi.org/10.1504/IJBRA.2009.029044
11	Sree, K., & Babu, R. (2010). Identification of promoter region in genomic DNA using cellular automata based text clustering. International Arab Journal of Information Technology.
12	Sree, P. K. (2013). An enhanced SLA based framework for bulk provisioning in telecommunication network. International Journal of Advanced Research in Computer and Communication Engineering.
13	Sree, P. K. (2013). HMACA: Towards proposing cellular automata based tool for protein coding, promoter region identification and protein structure prediction. International Journal of Research in Computer Applications & Information Technology.
14	Pokkuluri, K. S., Babu, I. R., & Usha Devi, N. S. S. S. N. (2013). AIS-PRMACA: Artificial immune system based multiple attractor cellular automata for strengthening PRMACA, promoter region identification. SIJ Transactions on Computer Science Engineering & Its Applications. https://doi.org/10.9756/SIJCSEA/V1I4/0104530101
15	Pokkuluri, K. S., Babu, I. R., & Usha Devi, N. S. S. S. N. (2013). AIS-PSMACA: Towards proposing an artificial immune system for strengthening PSMACA: An automated protein structure prediction using multiple attractor cellular automata. Global Journal of Computer Science and Technology.
16	Srinivasu, N., Samdani, S. M., & Kiran, L. S. (2014). Asynchronous data access and transaction decomposition in distributed databases. International Journal of Advanced Research in Computer Science.
17	Pokkuluri, K. S., Babu, I. R., & Nedunuri, S. S. S. N. U. D. (2014). IN-MACA-MCC: Integrated multiple attractor cellular automata with modified clonal classifier for human protein coding and promoter prediction. Advances in Bioinformatics. https://doi.org/10.1155/2014/261362
18	Pokkuluri, K. S. (2014). Cellular automata in splice site prediction. MOJ Proteomics & Bioinformatics. https://doi.org/10.15406/MOJPB.2014.01.00013
19	Pokkuluri, K. S., Babu, I. R., & Usha Devi, N. (2014). A fast multiple attractor cellular automata with modified clonal classifier for coding region prediction in human genome. Journal of Bioinformatics and Intelligent Control. https://doi.org/10.1166/JBIC.2014.1077
20	Pokkuluri, K. S., Babu, I. R., & Usha Devi, N. (2014). A fast multiple attractor cellular automata with modified clonal classifier promoter region prediction in eukaryotes. Journal of Bioinformatics and Intelligent Control. https://doi.org/10.1166/JBIC.2014.1077
21	Pokkuluri, K. S., & Babu, I. R. (2014). AIX-MACA-Y multiple attractor cellular automata based clonal classifier for promoter and protein coding region prediction. Journal of Bioinformatics and Intelligent Control. https://doi.org/10.1166/JBIC.2014.1071
22	Simulation analysis on network layer attacks in wireless mesh networks. (2018). International Journal of Engineering and Technology.
23	Pokkuluri, K. S. (2019). Deep learning mechanism augmented with 16-hybrid cellular automata for secondary structure prediction. International Journal of Innovative Technology and Exploring Engineering. https://doi.org/10.35940/IJITEE.B6458.129219
24	Pokkuluri, K. S. (2019). Gold price prediction using eight neighborhood non linear cellular automata. International Journal of Innovative Technology and Exploring Engineering. https://doi.org/10.35940/IJITEE.B7727.129219
25	Kiran, K. U., Shakeela, S., & Pavan Kalyan, G. S. R. (2020). Framework for environment quality monitoring using radial support vector regression. Journal of Computational and Theoretical Nanoscience. https://doi.org/10.1166/JCTN.2020.8866
26	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2020). COVID-19 hotspot trend prediction using hybrid cellular automata in India. Engineering Science & Technology. https://doi.org/10.37256/EST.212021610
27	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2020). A novel cellular automata classifier for COVID-19 prediction. Journal of Health Sciences. https://doi.org/10.17532/JHSCI.2020.907
28	Pokkuluri, K. S., Usha Devi, N. S. S. S. N., et al. (2020). Deep convolution network for COVID-19 death rate prediction. i-manager's Journal on Information Technology, 9(1). https://doi.org/10.26634/JIT.9.1.17254
29	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2021). A secure cellular automata integrated deep learning mechanism for health informatics. International Arab Journal of Information Technology. https://doi.org/10.34028/IAJIT/18/6/5
30	Behdenna, S., Belalem, G., & Barigou, F. (2022). An ontology-based approach to enhance explicit aspect extraction in standard Arabic reviews. International Journal of Computing and Digital Systems. https://doi.org/10.12785/IJCDS/110123
31	Mangalampalli, S., & Pokkuluri, K. S. (2022). An effective workflow scheduling algorithm in cloud computing using cat swarm optimization. ECS Transactions. https://doi.org/10.1149/10701.2523ECST
32	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2022). Crop disease prediction with convolution neural network (CNN) augmented with cellular automata. International Arab Journal of Information Technology, 19(5). https://doi.org/10.34028/IAJIT/19/5/8
33	Pokkuluri, K. S., Shalem Raju, P. J. R., & Kasula, K. V. D. (2022). Digital image watermarking based on hybrid FRT-HD-DWT domain and flamingo search optimisation. International Journal of Computational Vision and Robotics. https://doi.org/10.1504/IJCVR.2022.10050520
34	Prasad, M., Raja Rao, P. B. V., & Ramana, M. C. V. (2022). Fog-based data analytics scheme using edge affinity-based management. NeuroQuantology.
35	Begum, S. G., et al. (2023). Drug recommendation using recurrent neural networks augmented with cellular automata. BOHR International Journal of Internet of Things, Artificial Intelligence and Machine Learning. https://doi.org/10.54646/BIJIAM.2023.13
36	Mangalampalli, S. S., Karri, G. R., & Satish, G. N. (2023). SLA based workflow scheduling algorithm in cloud computing using Harris Hawks optimization. EAI Endorsed Transactions on Scalable Information Systems. https://doi.org/10.4108/EETSIS.4005
37	Pokkuluri, K. S. (2023). Machine learning for quality in health care: A comprehensive review. Biomedical Journal of Scientific & Technical Research. https://doi.org/10.26717/BJSTR.2023.51.008138
38	Pokkuluri, K. S. (2023). Deep learning in bioinformatics: Current advances and future prospects. Biomedical Journal of Scientific & Technical Research.
39	Pokkuluri, K. S., Prasad, M., & Shalem Raju, P. J. R. (2023). A comprehensive analysis on risk prediction of heart disease using machine learning models. International Journal on Recent and Innovation Trends in Computing and Communication. https://doi.org/10.17762/IJRITCC.V11I11S.8295
40	Prasad, M., Sudha Rani, P. R., & Ramana, C. V. (2023). Blockchain-enabled on-path caching for efficient and reliable content delivery in information-centric networks. International Journal on Recent and Innovation Trends in Computing and Communication. https://doi.org/10.17762/IJRITCC.V11I9.8397
41	Rapaka, A., Mallela, R. B., & Thammuluri, R. (2023). A comprehensive survey of convolutional neural networks for skin cancer classification and prediction. International Journal on Recent and Innovation Trends in Computing and Communication. https://doi.org/10.17762/IJRITCC.V11I11S.8085
42	Pokkuluri, K. S. (2023). Deep learning for heart attack prediction. Biomedical Journal of Scientific & Technical Research. https://doi.org/10.26717/BJSTR.2023.54.008522
43	Prasad, P. S., Sangeetha, T., & Reddy, V. K. (2023). A novel approach for detecting anomalies in clusters using soft computing techniques. AIP Conference Proceedings. https://doi.org/10.1063/5.0123212
44	Raju, P. J. R. S., Kiran, K. V. D., & Pokkuluri, K. S. (2023). Digital image watermarking based on hybrid FRT-HD-DWT domain and flamingo search optimisation. International Journal of Computational Vision and Robotics. https://doi.org/10.1504/IJCVR.2023.134319
45	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2023). Employee attrition prediction using KNN machine learning algorithm. SSRN Electronic Journal. https://doi.org/10.2139/SSRN.4452350
46	Ajay, A., et al. (2024). Collaborative intelligence for IoT: Decentralized net security and confidentiality. Journal of Intelligent Systems and Internet of Things. https://doi.org/10.54216/JISIOT.130216
47	Alzubi, J. A., et al. (2024). A robust authentication and trust detection with privacy preservation of data for fog computing in VANET using adaptive deep neural network. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3486811
48	Cheng, Y., Vijayaraj, A., & Rateb, R. (2024). Vehicular fog resource allocation approach for VANETs based on deep adaptive reinforcement learning combined with heuristic information. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3455168
49	D'Souza, M., Nimma, D., & Kongala, L. (2024). Multiclass osteoporosis detection: Enhancing accuracy with woodpecker-optimized CNN-XGBoost. International Journal of Advanced Computer Science and Applications, 15(8). https://doi.org/10.14569/IJACSA.2024.0150889
50	Hu, W., Pokkuluri, K. S., & Palanisamy, P. (2024). RSSI-based 3D wireless sensor node localization using hybrid T cell immune and lotus optimization. Computers, Materials and Continua. https://doi.org/10.32604/CMC.2024.055561
51	Jia, J., Kumarasamy, S. S., & Wang, F. (2024). A robust authentication and trust detection with privacy preservation of data for fog computing in VANET using adaptive deep neural network. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3486811
52	Mangalampalli, S. S., Karri, G. R., & Chakrabarti, T. (2024). An energy and temperature aware deep reinforcement learning workflow scheduler in cloud computing. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3488965
53	Menon, S., Addula, S. R., & Soni, A. (2024). Streamlining task planning systems for improved enactment in contemporary computing surroundings. SN Computer Science. https://doi.org/10.1007/S42979-024-03267-5
54	Mohanapriya, D., Chepur, J., & Subbulakshmi, R. (2024). Investigation of medication reviews and the identification of adverse drug reactions using machine learning algorithms. Measurement: Sensors. https://doi.org/10.1016/J.MEASEN.2024.101240
55	Pokkuluri, K. S. (2024). Convolutional neural networks for enhancing clinical decision-making. Biomedical Journal of Scientific & Technical Research. https://doi.org/10.26717/BJSTR.2024.56.008859
56	Pokkuluri, K. S. (2024). Fuzzy horizon: Unveiling the fog of uncertainty with cognitive cartography and fuzzy logic fusion. Communications on Applied Nonlinear Analysis. https://doi.org/10.52783/CANA.V31.1461
57	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2024). 3D convolutional neural networks for predicting protein structure for improved drug recommendation. EAI Endorsed Transactions on Pervasive Health and Technology. https://doi.org/10.4108/EETPHT.10.5685
58	Pokkuluri, K. S. (2024). Auto encoders with cellular automata for anomaly detection. Journal of Electrical Systems. https://doi.org/10.52783/JES.1131
59	Pokkuluri, K. S. (2024). Convolutional neural networks for enhancing clinical decision-making. Biomedical Journal of Scientific & Technical Research.
60	Raja Rao, P. B. V. (2024). Generic framework for vehicle identification system with deep learning models. Journal of Electrical Systems. https://doi.org/10.52783/JES.1440
61	Veera V Rama Rao, M. (2024). Optimizing breast cancer diagnosis with advanced deep learning techniques in medical imaging. Journal of Electrical Systems. https://doi.org/10.52783/JES.1461
62	Veera V Rama Rao, M. (2024). Enhancing network security: Leveraging machine learning for intrusion detection. Journal of Electrical Systems. https://doi.org/10.52783/JES.1460
63	Prem Kumar, P. S. (2024). 3D convolutional neural networks for video recognition. Communications on Applied Nonlinear Analysis, 32. https://doi.org/10.52783/CANA.V32.2205
64	Amutha, M., Lokeshwaran, K., & Yalawar, M. S. (2024). Green AI revolution machine learning for environmental-friendly communication networks. Journal of Environmental Protection and Ecology.
65	Sharmila, K. S., Revathi, S. T., & Sree, P. K. (2024). A systematic review on drug-to-drug interaction prediction and cryptographic mechanism for secure drug discovery using AI techniques. International Journal on Artificial Intelligence Tools. https://doi.org/10.1142/S0218213024500039
66	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2024). Enhancing image segmentation accuracy using deep learning techniques. Journal of Advanced Research in Applied Sciences and Engineering Technology, 49(1), 139-148. https://doi.org/10.37934/ARASET.49.1.139148
67	Veera V Rama Rao, M., Pokkuluri, K. S., & Shankar, A. (2024). A secured and energy-efficient system for patient e-healthcare monitoring using the Internet of Medical Things (IoMT). Data & Metadata. https://doi.org/10.56294/DM2024368
68	Ramesh Babu, G., Varma Chintalapati, P., & Vadapalli, V. K. S. K. S. (2024). Design and implementation of a dynamic IoT cloud based processing platform. Proceedings on Engineering Sciences. https://doi.org/10.24874/PES.SI.25.03B.013
69	Alzubi, J. A., Pokkuluri, K. S., & Arunachalam, K. (2025). A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network. Scientific Reports. https://doi.org/10.1038/S41598-025-02144-2
70	Chandanan, A. K., Rani, M., & Roy, V. (2025). Revolutionizing cardiac prediction based on fog-cloud-IoT integrated heart disease model. Scalable Computing.
71	Dash, B., Macedo, V. D. J., Sethi, K. C., et al. (2025). Optimizing time and cost in construction under uncertainty: A fuzzy-driven NSGA-III optimization approach. Asian Journal of Civil Engineering. https://doi.org/10.1007/S42107-025-01364-1
72	Joshi, S., Mahanthi, B. L., & Sahu, R. (2025). Integrating LSTM and CNN for stock market prediction: A dynamic machine learning approach. Journal of Artificial Intelligence and Technology. https://doi.org/10.37965/JAIT.2025.0652
73	Manusha, S., Varma, N., & Elayaperumal, S. (2025). Altered microbiome influence on the enteric neuromuscular system in amyotrophic lateral sclerosis (ALS). International Review of Neurobiology. https://doi.org/10.1016/BS.IRN.2025.04.006
74	Pala, S., Maddula, P., & Yadavalli, R. (2025). Detection and avoidance of black-hole attack in mobile adhoc network using bee-ad-hoc on-demand distance vector. IAES International Journal of Artificial Intelligence. https://doi.org/10.11591/IJAI.V14.I1.PP822-832
75	Pokkuluri, K. S. (2025). Machine learning-based prediction of energy consumption in smart buildings for sustainable energy management. Journal of Information Systems Engineering & Management, 10(13S). https://doi.org/10.52783/JISEM.V10I13S.2000
76	Pokkuluri, K. S., Chauhan, T. R., & Sethi, K. C. (2025). Opposition-based multi-objective ant colony optimization framework for sustainable retrofitting: Time-cost-energy-risk trade-offs. Asian Journal of Civil Engineering. https://doi.org/10.1007/S42107-025-01309-8
77	Pokkuluri, K. S., Mangalampalli, S. S., & Usha Devi, N. S. S. S. N. (2025). Predicting oil reservoir behavior with convolutional neural networks. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-8156-4.CH009
78	Pokkuluri, K. S., Mounika, T., & Krishna, B. M. (2025). Disaster management based on biodiversity conservation using remote sensing data analysis using machine learning model. Remote Sensing in Earth Systems Sciences. https://doi.org/10.1007/S41976-024-00188-Y
79	Pokkuluri, K. S., Nagendra, D. P., & Manjunath, T. C. (2025). Optimization of sustainable retrofitting using OBL-MOTLBO: A multi-objective approach to time, cost, and environmental trade-offs. Asian Journal of Civil Engineering. https://doi.org/10.1007/S42107-025-01479-5
80	Pokkuluri, K. S., Sarkar, P., & Roy, V. (2025). Intelligent reasonable optimization for virtual machine provisioning in hybrid cloud using fuzzy AHP and cost-effective autoscaling. SN Computer Science. https://doi.org/10.1007/S42979-025-04287-5
81	Prasad, M., Ajita Lakshmi, K., & Murthy, Ch. S. V. V. S. N. (2025). A novel ALU using distributed arithmetic for real time signal processing application. Proceedings on Engineering Sciences. https://doi.org/10.24874/PES07.01B.011
82	Prasad, M., Challa, N., & Raju, P. (2025). Air quality prediction using genetic algorithm-based feature selection and machine learning techniques for sustainable environmental management. IOP Conference Series: Earth and Environmental Science, 1529(1), 012001. https://doi.org/10.1088/1755-1315/1529/1/012001
83	Prasad, M., Raja Rao, P. B. V., & Lakshmi, K. A. (2025). BISEARCHINS-driven eco-friendly hybrid rideshare system for sustainable and efficient urban transportation. Proceedings on Engineering Sciences. https://doi.org/10.24874/PES07.03A.025
84	Ramkumar, B. V., Savitha, S., & Kirubanand, V. B. (2025). Adaptive fuzzy heuristic algorithm for dynamic data mining in IoT integrated big data environments. Journal of Fuzzy Extension and Applications. https://doi.org/10.22105/JFEA.2024.484955.1676
85	Rebecca, B., Sandhya, A., & Krishna, B. M. (2025). Marine life ecosystem analysis based on climate change detection using deep learning algorithms. Remote Sensing in Earth Systems Sciences. https://doi.org/10.1007/S41976-025-00212-9
86	Raju, P. J. R. S., Sree, P. K., & Murty, P. T. S. (2025). A novel approach for watermarking medical images using electronic patient record data and a multi-bit-quantisation modulation method. International Journal of Intelligent Engineering Informatics. https://doi.org/10.1504/IJIEI.2025.146687
87	Sharmila, K. S., Revathi, S. T., & Sree, P. K. (2025). DDINet: Drug-drug interaction prediction network based on multi-molecular fingerprint features and multi-head attention centered weighted autoencoder. Journal of Bioinformatics and Computational Biology. https://doi.org/10.1142/S0219720025500039
88	Shubha, S., Venu, D., & Saisandeep, B. (2025). Navigating efficiency: Evaluating wireless ad hoc network protocols with NS-3. Sigma Journal of Engineering and Natural Sciences. https://doi.org/10.14744/SIGMA.2025.00079
89	Sivakumar, R., Prasad, K., & Nayak, B. B. (2025). Augmented and virtual reality based human resource management and its impact on organizational sustainability. WSEAS Transactions on Business and Economics. https://doi.org/10.37394/23207.2025.22.86
90	Sivakumar, R., Singh, K., & Mohapatra, M. R. (2025). Urban air quality monitoring system enhanced by IoT for comprehensive deployment, data collection, and environmental impact analysis. WSEAS Transactions on Environment and Development. https://doi.org/10.37394/232015.2025.21.33
91	Gupta, S. (2025). Predicting future rainfall with various machine learning models. Journal of Information Systems Engineering & Management, 10(3S). https://doi.org/10.52783/JISEM.V10I3S.354
92	Varma Ch, P., Ramesh Babu, G., & Venkata Ramana, Ch. (2025). High accuracy classification of Parkinson's disease detection using RNN-graph-LSTM. Proceedings on Engineering Sciences. https://doi.org/10.24874/PES07.01B.010
93	Soni Sharmila, K., Thanga Revathi, S., & Sree, P. K. (2026). A systematic review on drug-to-drug interaction prediction and cryptographic mechanism for secure drug discovery using AI techniques [Corrigendum]. International Journal on Artificial Intelligence Tools, 33, 2450003. https://doi.org/10.1142/S0218213026920016
94	Kadimi, S. S., Revathi, S. T., & Sree, P. K. (2026). Capsule enclosed coordinate attention based dual batch depthwise convolutional knowledge distillation model for drug-drug interaction prediction. Molecular Diversity. https://doi.org/10.1007/S11030-025-11433-X

 

Table 2: Book Chapters

S.No	APA Citation
1	Mangalampalli, S., Pokkuluri, K. S., & Mangalampalli, V. K. (2022). Energy efficient VM consolidation technique in cloud computing using cat swarm optimization. In Machine intelligence and data science applications: MIDAS (LNDECT, Vol. 132). Springer. https://doi.org/10.1007/978-981-19-2347-0_36
2	Mangalampalli, S., & Sree, P. K. (2022). An effective VM consolidation mechanism by using the hybridization of PSO and cuckoo search algorithms. In Computational intelligence in data mining: ICCIDM (SIST, Vol. 281). Springer. https://doi.org/10.1007/978-981-16-9447-9_37
3	Mangalampalli, S., & Pokkuluri, K. S. (2022). An efficient workflow scheduling algorithm in cloud computing using cuckoo search and PSO algorithms. In Innovations in computer science and engineering: ICICSE (LNNS, Vol. 385). Springer. https://doi.org/10.1007/978-981-16-8987-1_15
4	Pokkuluri, K. S., Usha Devi, N. S. S. S. N., & Mangalampalli, S. (2022). DLCP: A robust deep learning with non-linear CA mechanism for lung cancer prediction. In Innovations in computer science and engineering: ICICSE (LNNS, Vol. 385). Springer. https://doi.org/10.1007/978-981-16-8987-1_31
5	Pokkuluri, K. S., Usha Devi, N. S. S. S. N., & Mangalampalli, S. (2022). DLHAP: A novel deep learning with hybrid CA mechanism for heart attack prediction. In Innovations in computer science and engineering: ICICSE (LNNS, Vol. 385). Springer. https://doi.org/10.1007/978-981-16-8987-1_32
6	Pokkuluri, K. S., & Usha Devi, N. (2023). Review on healthcare quality using machine learning methods. In Internet of Things and advanced application in healthcare. IGI Global. https://doi.org/10.4018/979-8-3693-0876-9.CH024
7	Raja Rao, P. B. V., Prasad, M., & Satyanarayana Murty, P. T. (2023). Enhancing the MANET AODV forecast of a broken link with LBP. In Intelligent systems and sustainable computing: Proceedings of ICISSC (SIST, Vol. 363). Springer. https://doi.org/10.1007/978-981-99-4717-1_6
8	Revathy, G., Sree, P. K., & Vadivu, S. S. (2023). Visual learning with dynamic recall. In Soft computing and signal processing: Proceedings of ICSCSP (SIST, Vol. 313). Springer. https://doi.org/10.1007/978-981-19-8669-7_11
9	Satyanarayana Murty, P. T., Prasad, M., & Phaneendra Varma, C. (2023). A hybrid intelligent cryptography algorithm for distributed big data storage in cloud computing security. In Multi-disciplinary trends in AI: MIWAI (LNAI, Vol. 14078). Springer. https://doi.org/10.1007/978-3-031-36402-0_59
10	Khang, A., Rath, K. C., & Panda, S. K. (2023). Revolutionizing agriculture. In Handbook of research on microbial tools for environmental waste management. IGI Global. https://doi.org/10.4018/978-1-6684-9231-4.CH001
11	Chintalapati, P. V., Babu, G. R., & Kumar, G. S. (2023). Usage of AI techniques for cyberthreat security system in Android mobile devices. In Proceedings of ICICC (LNNS, Vol. 703). Springer. https://doi.org/10.1007/978-981-99-3315-0_33
12	Pokkuluri, K. S., Chakrabarti, P., & Usha Devi, N. S. S. S. N. (2024). Hybrid cellular automata with CNN for the prediction of secondary structure of protein. In Innovations in data analytics: Selected papers of ICIDA (LNNS, Vol. 1005). Springer. https://doi.org/10.1007/978-981-97-4928-7_24
13	Pokkuluri, K. S., Chakrabarti, P., & Usha Devi, N. S. S. S. N. (2024). Drug recommendations using support vector machine. In Innovations in data analytics: Selected papers of ICIDA (LNNS, Vol. 1005). Springer. https://doi.org/10.1007/978-981-97-4928-7_13
14	Pokkuluri, K. S., & Khang, A. (2024). Deep learning for identification of behavioral changes. In Social, health, and environmental infrastructures for economic growth. IGI Global. https://doi.org/10.4018/979-8-3693-6055-2.CH004
15	Pokkuluri, K. S., Usha Devi, N., & Khang, A. (2024). Quantum precision in medical imaging. In The quantum evolution. CRC Press. https://doi.org/10.1201/9781032642079-12
16	Pokkuluri, K. S., Usha Devi, N., & Khang, A. (2024). Quantum-powered hate speech detection. In The quantum evolution. CRC Press. https://doi.org/10.1201/9781032642079-19
17	Pokkuluri, K. S., Usha Devi, N. S. S. S. N., & Chakrabarti, P. (2024). Protein structure prediction using convolutional neural networks augmented with cellular automata. In Computational intelligence: Theory and applications.
18	Gantayat, S. S., Pimple, K. M., & Pokkuluri, K. S. (2024). IoMT type-2 fuzzy logic implementation. In Advances in fuzzy-based Internet of Medical Things (IoMT). Wiley. https://doi.org/10.1002/9781394242252.CH12
19	Pokkuluri, K. S., Khang, A., & Usha Devi, N. S. S. S. N. (2024). Long short-term memory networks for automated waste treatment augmented with IoT and bioelectric sensors. In Handbook of research on microbial tools for environmental waste management. IGI Global. https://doi.org/10.4018/979-8-3693-6016-3.CH016
20	Pokkuluri, K. S., Khang, A., & Usha Devi, N. S. S. S. N. (2024). Integration of machine learning augmented with biosensors for enhanced water quality monitoring. In Handbook of research on microbial tools for environmental waste management. IGI Global. https://doi.org/10.4018/979-8-3693-2069-3.CH009
21	Pokkuluri, K. S., Khang, A., & Usha Devi, N. S. S. S. N. (2024). Enhancing aquaculture efficiency. In Handbook of research on microbial tools for environmental waste management. IGI Global. https://doi.org/10.4018/979-8-3693-2069-3.CH022
22	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2024). CulinarySpectra. In Handbook of research on holistic optimization techniques in the hospitality, tourism, and travel industry. IGI Global. https://doi.org/10.4018/979-8-3693-1814-0.CH003
23	Komperla, R. C. A., Pokkuluri, K. S., & Rahila, J. (2024). Revolutionizing biometrics with AI-enhanced X-ray and MRI analysis. In Internet of Things and advanced application in healthcare. IGI Global. https://doi.org/10.4018/979-8-3693-5946-4.CH001
24	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2024). Designing LSTM networks for emotion modelling. In Identifying, treating, and preventing childhood trauma in rural communities. IGI Global. https://doi.org/10.4018/979-8-3693-1910-9.CH006
25	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2024). Deep insights. In Advanced pharmacological uses of medicinal plants and natural products. IGI Global. https://doi.org/10.4018/979-8-3693-3218-4.CH012
26	Pokkuluri, K. S., & Usha Devi, N. (2024). Decoding disease. In Advanced pharmacological uses of medicinal plants and natural products. IGI Global. https://doi.org/10.4018/979-8-3693-3218-4.CH010
27	Sree, P. K., Usha Devi, N. S., & Raja Rao, P. (2024). Drug recommendations using a reviews and sentiment analysis by RNN. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 536). Springer. https://doi.org/10.1007/978-3-031-48888-7_11
28	Babu, G. R., Chintalapati, P. V., & Kumar, K. S. (2024). An advanced artificial intelligence-driven smart home towards ontology-based energy efficiency management system. In Innovations in data analytics: Selected papers of ICIDA (LNNS, Vol. 972). Springer. https://doi.org/10.1007/978-981-97-3466-5_24
29	Labhane, S., Radha, J., & Srivastava, P. (2024). Quantum-inspired deep learning for networked data analysis with quantum networked discord and allies. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-5832-0.CH002
30	Uma Maheswari, et al. (2024). Scaling AI with quantum network models for back pain genetic architecture. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-5832-0.CH019
31	Sangeerani Devi, A., Saffina, C., & Tanty, G. (2024). Collective dynamics of 'small-world' networks enhanced by quantum technology for trusted AI transactions. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-5832-0.CH009
32	Babu, G. R., Chintalapati, P. V., & Maneesha, B. (2025). A secure and efficient cloud storage system using advanced encryption standard algorithm for data protection. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 598). Springer. https://doi.org/10.1007/978-3-031-77078-4_6
33	Chintalapati, P. V., Babu, G. R., & Anoch, B. (2025). Detection of autism spectrum disorder using optimized extreme learning machine technique. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 598). Springer. https://doi.org/10.1007/978-3-031-77078-4_22
34	Kavita, K., Suresh Kumar, K., & Pokkuluri, K. S. (2025). Simulation and implementation of English speech recognition by NLP. In Integrating neurocomputing with artificial intelligence. Wiley. https://doi.org/10.1002/9781394335718.CH9
35	Khang, A., Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2025). Deep learning augmented with robotics in pipeline inspection and leak detection for the oil and gas industry. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-8156-4.CH013
36	Pbv, R. R., Pokkuluri, K. S., & Karunasri, A. (2025). Ensemble fusion for enhanced malicious URL detection by integrating machine learning and deep learning techniques. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 597). Springer. https://doi.org/10.1007/978-3-031-77075-3_27
37	Pbv, R. R., Prasad, M., & Rao, B. V. (2025). An efficient sentiment classification model using fusion of BERT and deep learning RNN variants. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 597). Springer. https://doi.org/10.1007/978-3-031-77075-3_22
38	Pokkuluri, K. S., Chandrasekar, A., & Saivaraju, A. (2025). Charting the course. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3373-1504-1.CH002
39	Pokkuluri, K. S., Mangalampalli, S. S., & Usha Devi, N. S. S. S. N. (2025). Predicting oil reservoir behavior with convolutional neural networks. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-8156-4.CH009
40	Pokkuluri, K. S., Phaneendra Varma, C. H., & Shalem Raju, P. J. R. (2025). Identification of different medicinal plants using machine learning and image processing. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 597). Springer. https://doi.org/10.1007/978-3-031-77075-3_7
41	Pokkuluri, K. S., Sivakoti, R., & Usha Devi, N. S. S. S. N. (2025). Hate speech detection using recurrent neural networks (RNN). In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 599). Springer. https://doi.org/10.1007/978-3-031-77081-4_5
42	Pokkuluri, K. S., Subha, A. D. S., & Shalem Raju, P. J. R. (2025). Fake news detection using ML algorithms. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 599). Springer. https://doi.org/10.1007/978-3-031-77081-4_4
43	Pokkuluri, K. S., Gurujukota, R. B., & Murthy, P. T. S. (2025). Generative adversarial networks (GANs) for drug discovery. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 599). Springer. https://doi.org/10.1007/978-3-031-77081-4_21
44	Pokkuluri, K. S., Usha Devi, N. S. S. S. N., & Elayaperumal, S. (2025). Enhanced oil recovery strategy prediction using temporal convolutional network. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-8156-4.CH003
45	Pokkuluri, K. S., Usha Devi, N. S. S. S. N., & Khang, A. (2025). Deforestation and forest monitoring with CNN and RNN. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3373-1399-3.CH008
46	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2025). CNN's augmented with IoT for traffic optimization and signal regulation. In Proceedings of international conference on artificial intelligence and smart energy. Springer. https://doi.org/10.1007/978-3-031-74885-1_22
47	Prasad, M., Ramadevi, S., & Lakshmi, K. A. (2025). A study on fatty liver segmentation and classification as revealed by CT scans. In Intelligent systems and sustainable computing: Proceedings of ICISSC (SIST, Vol. 417). Springer. https://doi.org/10.1007/978-981-97-8355-7_36
48	Revathy, G., Pokkuluri, K. S., & Gokulraj, S. (2025). Electric vehicle energy management using fuzzy logics and machine learning. In Multimedia and sensory input for augmented, mixed, and virtual reality. IGI Global. https://doi.org/10.4018/979-8-3693-7352-1.CH010
49	Salini, Y., Pokkuluri, K. S., & Joseph, M. (2025). Machine learning-based swarm optimization for residential demand-based electricity. In Sustainable smart homes and buildings with Internet of Things.
50	Shalem Raju, P. J. R., Prasad, M., & Gompa, N. S. (2025). Predictive modeling for job recommendations: Harnessing the power of KNN, SVM, and LR algorithms. In ICT systems and sustainability: Proceedings of ICT4SD (LNNS, Vol. 1159). Springer. https://doi.org/10.1007/978-981-97-8526-1_9
51	Sree, P. K., Tejaswi, M., & Raju, P. J. R. S. (2025). Crime detection with variational autoencoders. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 598). Springer. https://doi.org/10.1007/978-3-031-77078-4_8
52	Sree, P. K., Prasad, M., & Babu, G. R. (2025). Auto encoders with cellular automata for anomaly detection. In Cognitive computing and cyber physical systems: EAI IC4S (LNICST, Vol. 598). Springer. https://doi.org/10.1007/978-3-031-77078-4_28
53	Pokkuluri, K. S., Kolikipogu, R., & Mamta. (2025). Construction and simulation of hybrid neural network and LSTM to language process model. In Integrating neurocomputing with artificial intelligence.
54	Pokkuluri, K. S., & Usha Devi, N. S. S. S. N. (2025). Deep learning for threat detection and analysis. In Privacy and security policies in big data. IGI Global. https://doi.org/10.4018/979-8-3693-6371-3.CH002

 

Table 3: Conference Papers

S.No	APA Citation
1	Sree, P. K., & Babu, I. R. (2008). Towards a cellular automata based network intrusion detection system with power level metric in wireless adhoc networks (IDFADNWCA). In Proceedings of ICACTE 2008. IEEE. https://doi.org/10.1109/ICACTE.2008.160
2	Sree, P. K., & Babu, I. R. (2008). Investigating cellular automata based network intrusion detection system for fixed networks (NIDWCA). In Proceedings of ICACTE 2008. IEEE. https://doi.org/10.1109/ICACTE.2008.159
3	Sree, P. K. (2008). An efficient parallel IP lookup technique for IPv6 routers using multiple hashing with ternary marker storage with cellular automata and control prefix expansion. In KMICE 2008 - Knowledge Management International Conference.
4	Pokkuluri, K. S., Raju, G. V. S., & Usha Devi, N. S. S. S. N. (2013). Cellular automata based feedback mechanism in strengthening biological sequence analysis approach to robotic soccer. ArXiv.
5	Nanneti, I. N., & Sree, P. K. (2013). A novel approach to automatic age and gender recognition by using neural network system.
6	Pokkuluri, K. S., Babu, I. R., & Nedunuri, S. S. S. N. U. D. (2014). PRMACA: A promoter region identification using multiple attractor cellular automata (MACA). In Advances in intelligent systems and computing. Springer. https://doi.org/10.1007/978-3-319-03107-1_42
7	Kiran Sree, P., Babu, I. R., & Usha Devi, N. S. S. S. N. (2014). AIS-MACA-Z: MACA based clonal classifier for splicing site, protein coding and promoter region identification in eukaryotes. ArXiv.
8	Pokkuluri, K. S., & Devi, S. S. S. N. U. N. (2015). RTWPCAMARM: A dynamic real time weather prediction system with 8 neighborhood hybrid cellular automata and modified association rule mining. In Proceedings of ICACCI 2015. IEEE. https://doi.org/10.1109/ICACCI.2015.7275609
9	Kiran, P., & Ramesh, I. (2015). Investigating cellular automata based network intrusion detection system for fixed networks (NIDWCA).
10	Aboshosha, A., Pokkuluri, K. S., & Solaiman, B. (2015). GVIP-Volume 8-Issue 2. https://doi.org/10.13140/RG.2.1.4990.4083
11	Mangalampalli, S., Reedy, K. G., & Raju, V. P. (2017). An effective analysis on various scheduling algorithms in cloud computing. In Proceedings of ICICI 2017. IEEE. https://doi.org/10.1109/ICICI.2017.8365274
12	Mohan, R., & Sree, P. K. (2017). An extensive survey on deep learning applications.
13	Sree, P. K., Rao, P. S. V. S., & Devi, S. S. S. N. U. N. (2017). CDLGP: A novel unsupervised classifier using deep learning for gene prediction. In Proceedings of ICPCSI 2017. IEEE. https://doi.org/10.1109/ICPCSI.2017.8392232
14	Sree, P. K., Devi, S. S. S. N. U. N., & Sudheer, M. S. (2017). A robust deep learning mechanism augmented with cellular automata for DNA computing. In Proceedings of ICPCSI 2017. IEEE. https://doi.org/10.1109/ICPCSI.2017.8391921
15	Reddy, Ch. S., Sagar, B., & Reddy, S. S. (2018). The structural design of the multistorey building.
16	Kiran, V., Kumar, N., & Reddy, V. (2018). Paediatric femoral neck fractures: Our 5 years of experience. International Journal of Orthopaedics.
17	Mishra, A. (2019). An artificial intelligence based approach to determine the elongation% and ultimate tensile strength of friction stir welded dissimilar marine grade aluminium alloy joints.
18	Mohamed Iqbal, M., Chandra Kiran, P., & Shakthivel, R. (2020). LabVIEW-based virtual laboratories for electrical engineering education with real-time implementation. In Proceedings of ICSCSP 2020. Springer. https://doi.org/10.1007/978-981-15-2475-2_49
19	Mangalampalli, S., Sree, P. K., & Kocherla, R. T. (2021). Prioritized load balancer for minimization of VM and data transfer cost in cloud computing.
20	Pokkuluri, K. S. (2021). DLCDI: A novel deep learning mechanism for chronic diseases identification.
21	Mangalampalli, S., & Pokkuluri, K. S. (2022). Effective VM placement mechanism in cloud computing using cuckoo search optimization. In Proceedings of IC3P 2022. IEEE. https://doi.org/10.1109/IC3P52835.2022.00057
22	Ramesh Babu, G., Phaneendra Varma, Ch., & Kumar, G. S. C. (2022). A declarative systematic approach to machine learning. In Proceedings of SSTEPS 2022. IEEE. https://doi.org/10.1109/SSTEPS57475.2022.00034
23	Varma, C. P., Babu, G. R., & Sai, N. R. (2022). Usage of classifier ensemble for security enrichment in IDS. In Proceedings of ICACRS 2022. IEEE. https://doi.org/10.1109/ICACRS55517.2022.10029251
24	Maddula, P., Srikanth, P., & Murty, P. T. S. (2023). COVID-19 prediction with chest X-ray images using CNN. In Proceedings of IITCEE 2023. IEEE. https://doi.org/10.1109/IITCEE57236.2023.10090951
25	Pamarthi, N., Satyanarayana Murty, P. T., & Maram, B. (2023). A research study of heart health monitoring using deep learning and IoT. In Proceedings of IDICAIEI 2023. IEEE. https://doi.org/10.1109/IDICAIEI58380.2023.10406326
26	Mallesh, A. S., Pamarthi, N., & Maram, B. (2023). Smart system for early detection of agricultural plant diseases in the vegetation period. In Proceedings of IDICAIEI 2023. IEEE. https://doi.org/10.1109/IDICAIEI58380.2023.10406672
27	Sharmila, K. S., Revathi, S. T., & Sree, P. K. (2023). Enhancing drug-drug interaction prediction: A unified similarity-based neural network approach. In Proceedings of GCITC 2023. IEEE. https://doi.org/10.1109/GCITC60406.2023.10425844
28	Sharmila, K. S., Revathi, S. T., & Kiran Sree, P. (2023). Drug-drug interaction: An improved prediction approach based on convolutional neural networks. In Proceedings of ICSCNA 2023. IEEE. https://doi.org/10.1109/ICSCNA58489.2023.10370722
29	Sharmila, K. S., Revathi, S. T., & Pokkuluri, K. S. (2023). Convolution neural networks based lungs disease detection and severity classification. In Proceedings of ICCCI 2023. IEEE. https://doi.org/10.1109/ICCCI56745.2023.10128188
30	Sree, P. K., Chintalapati, P. V., & Raja Rao, P. B. V. (2023). Waste management detection using deep learning. In Proceedings of ICCIT 2023. IEEE. https://doi.org/10.1109/ICCIT58132.2023.10273898
31	Sree, P. K., Babu, G. R., & Prasad, M. (2023). Fake news detection using cellular automata based deep learning. In Proceedings of ICCIT 2023. IEEE. https://doi.org/10.1109/ICCIT58132.2023.10273875
32	Babu, G. R., Varma Chintalapati, P., & Ramana, C. V. (2023). A context sensitive with effective task migration in mobile cloud computing services. In Proceedings of ICCIT 2023. IEEE. https://doi.org/10.1109/ICCIT58132.2023.10273949
33	Pokkuluri, K. S., Sssn Usha Devi, N., & Ramesh Babu, G. (2024). Detection of vehicle crashes on roads using deep learning. In Proceedings of ICACCT 2024. IEEE. https://doi.org/10.1109/INCACCT61598.2024.10551202
34	Prasad, M., Lakshmi, K. A., & Das, G. S. (2024). A CNN and TF techniques development for efficient identification of floral recognition. In Proceedings of IC2PCT 2024. IEEE. https://doi.org/10.1109/IC2PCT60090.2024.10486528
35	Pbv, R. R., Prasad, M., & V V Satyanarayana, B. (2024). An efficient cancer detection model using ML and transfer learning techniques. In Proceedings of ICDCOT 2024. IEEE. https://doi.org/10.1109/ICDCOT61034.2024.10515383
36	Murty, P. T. S., Sree, P. K., & Vineetha, D. (2024). Detection and classification of potholes using CNN. In Proceedings of CCICT 2024. IEEE. https://doi.org/10.1109/CCICT62777.2024.00026
37	Prasad, M., Teja, A. L. S., & Pokkuluri, K. S. (2024). Emergency message prioritization and scheduling in vehicular ad hoc networks. In Proceedings of CCICT 2024. IEEE. https://doi.org/10.1109/CCICT62777.2024.00042
38	Chintalapati, P. V., Paluri, S. S., & Sree, P. K. (2024). A research model for automated prediction and analysis of job interview performance. In Proceedings of CCICT 2024. IEEE. https://doi.org/10.1109/CCICT62777.2024.00055
39	Shukla, T. D., Nimma, D., & Bala, B. K. (2024). Utilizing artificial intelligence for enhancing performance and preventing injuries in sports analytics. In Proceedings of IC-SIT 2024. IEEE. https://doi.org/10.1109/IC-SIT63503.2024.10862063
40	Pokkuluri, K. S., Nigam, N., & Chhaya. (2024). Efficient novel method for EEG signal classification in epileptic seizure identification using metaheuristic deep learning. In Proceedings of ICRASET 2024. IEEE. https://doi.org/10.1109/ICRASET63057.2024.10895075
41	Sree Pokkuluri, K., Aswini, P., & Adnan, K. (2024). Cluster head-based wireless sensor network sustainability algorithm. In Proceedings of IC3TES 2024. IEEE. https://doi.org/10.1109/IC3TES62412.2024.10877598
42	Rao, S. U. M., Prasad, M., & Aramanda, N. R. (2024). Leveraging deep learning and computer vision for accurate maritime vessel activity detection. In Proceedings of ICAITPR 2024. IEEE. https://doi.org/10.1109/ICAITPR63242.2024.10960125
43	Prasad, M., Challa, N., & Rapaka, A. (2024). Advancing air quality index (AQI) forecasting: Traditional, data-driven, and hybrid techniques. In Proceedings of ICMNWC 2024. IEEE. https://doi.org/10.1109/ICMNWC63764.2024.10872193
44	Musthafa, A. S., & Sree, P. K. (2024). Adaptive hybrid fraud detection system with personalized transaction profiling. In Proceedings of ICSCNA 2024. IEEE. https://doi.org/10.1109/ICSCNA63714.2024.10863971
45	Pokkuluri, K. S., Soni, N., & Sharma, D. (2024). Optimized fetal ECG feature extraction with genetic algorithm based heart rate detection. In Proceedings of ICTBIG 2024. IEEE. https://doi.org/10.1109/ICTBIG64922.2024.10911158
46	Kavarthapu, A., Sree, P. K., & Lakshmi, D. R. (2024). Review of various object detection and anomaly detection techniques. In International Conference on Advances in Computing, Control, and Telecommunication Technologies.
47	Prasad, M., Rao, R. P. B. V., & Sree, P. K. (2024). Currency denomination recognition using deep learning: A comprehensive study on Indian currency with convolutional neural networks. In International Conference on Advances in Computing, Control, and Telecommunication Technologies.
48	Babu, G. R., Ratnankitha, V. H., & Sree, P. K. (2024). An investigation of smartphone addiction with life satisfaction as a prediction effect of eyes and psychological health problems. In International Conference on Advances in Computing, Control, and Telecommunication Technologies.
49	Gudavalli, H., Kurada, R. R., & Pokkuluri, K. S. (2025). A comprehensive review of deep learning for disaster victim detection: Trends, challenges, and future directions. In Proceedings of ICAISS 2025. IEEE. https://doi.org/10.1109/ICAISS61471.2025.11041936
50	Harini, V., Srikanth, P., & Sree, P. K. (2025). Hybrid deep learning with multi-level context for pain assessment using physiological signals. In Proceedings of ICCSAI 2025. IEEE. https://doi.org/10.1109/ICCSAI64074.2025.11064490
51	Kusuma, A., Raju, P., & Pokkuluri, K. S. (2025). Uncertainty and explainability in AI for chronic kidney disease: A comprehensive review. In Proceedings of ICCMC 2025. IEEE. https://doi.org/10.1109/ICCMC65190.2025.11139940
52	Murthy, B. S., Lakshmi, K. A., & Raju, P. J. R. S. (2025). AgroVisionNet: A deep convolutional framework for multivariate crop yield forecasting in heterogeneous environments. In Proceedings of ICCRTEE 2025. IEEE. https://doi.org/10.1109/ICCRTEE64519.2025.11052937
53	Murthy, B. S., Pbv, R. R., & Kumar, K. S. (2025). Hybrid security framework and machine learning based anomaly detection for machine-to-machine communications. In Proceedings of ICCRTEE 2025. IEEE. https://doi.org/10.1109/ICCRTEE64519.2025.11053023
54	Pokkuluri, K. S., Awasthy, S. K., & M, U. A. S. (2025). Improving intrusion detection with fused IGAN-IDs and randomized tree classification for enhanced performance. In Proceedings of OTCON 2025. IEEE. https://doi.org/10.1109/OTCON65728.2025.11070937
55	Pokkuluri, K. S., Jain, K., & Navanitha, D. (2025). A unified knowledge base for drug label analysis using learning models, NLP, and IoT tasks. In Proceedings of OTCON 2025. IEEE. https://doi.org/10.1109/OTCON65728.2025.11070706
56	Pokkuluri, K. S., Kumar Chandanan, A., & Bhatt, N. (2025). Deep learning-enhanced intrusion detection and privacy preservation for IIoT networks. In Proceedings of ICDCECE 2025. IEEE. https://doi.org/10.1109/ICDCECE65353.2025.11035784
57	Pokkuluri, K. S., Sivanjani, M., & Rapaka, A. (2025). Deep learning-based detection of traffic accidents using CNN and VGG16 on accident and foggy image datasets. In Proceedings of ISACC 2025. IEEE. https://doi.org/10.1109/ISACC65211.2025.10969159
58	Raja Rao, P., Swathi, C., & Rapaka, A. (2025). Autonomous load balancing of optimized path selection for wireless mesh network. In Proceedings of AMATHE 2025. IEEE. https://doi.org/10.1109/AMATHE65477.2025.11081198
59	Sivanuja, M., Raju, P. J. R. S., & Sree, P. K. (2025). A novel ensemble-based deep learning framework combining CNN and transfer learning models for enhanced wildfire detection. In Proceedings of ICCRTEE 2025. IEEE. https://doi.org/10.1109/ICCRTEE64519.2025.11052908
60	Sivanuja, M., Raju, P. J. R. S., & Sree, P. K. (2025). Detecting wildfire hazards using convolutional neural networks. In Proceedings of ICCSAI 2025. IEEE. https://doi.org/10.1109/ICCSAI64074.2025.11063995
61	Sri, M. J., Rapaka, A., & Sree, P. K. (2025). Misinformation detection in social media using advanced transformer-based models through BERT and XLNet. In Proceedings of ICCMC 2025. IEEE. https://doi.org/10.1109/ICCMC65190.2025.11140944

 

Table 4: Books

S.No	APA Citation
1	Pokkuluri, K. S., & Khang, A. (2024). GRITEX SCEDEX, AIOCF, USA.