Research in AI and Machine Learning drives transformative advancements by developing intelligent systems capable of learning, adapting, and solving complex problems. Through innovations in algorithms, data analysis, and model interpretability, AI and ML research paves the way for impactful applications across diverse fields, from healthcare to finance.
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My research in Artificial Intelligence and Deep Learning focuses on developing advanced algorithms for machine learning, neural networks, and data-driven decision-making. I explore cutting-edge techniques to enhance model performance and solve complex problems in areas like natural language processing and computer vision.
My research in Artificial Intelligence and Deep Learning focuses on developing advanced algorithms for machine learning, neural networks, and data-driven decision-making. I explore cutting-edge techniques to enhance model performance and solve complex problems in areas like natural language processing and computer vision.
2026
2026
Ashok Polavarapu, M. Guduri, and M. Margala.“A Secured Synthetic Neuroanatomy for Epilepsy Recognition under Data Scarcity” Submitted to 17th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. (ACM BCB).
2025
2025
M. Guduri, Ashok Polavarapu, El Yabroudi, et al., “A Novel Framework on Cardiovascular Disease Prediction Using Transfer Learning Technique” in In: Lanka, S., Cabezuelo, A.S., Tugui, A. (eds) Trends in Sustainable Computing and Machine Intelligence. ICTSM 2025. Lecture Notes in Networks and Systems, vol 1755. Springer, Cham. doi: 10.1007/978-3-032-13177-5_7
Ashok Polavarapu, Manisha Guduri, and Martin Margala, “Hybrid Naval Combat Generative Adversarial Networks - XGBoost Framework for Adversary Recognition in Naval Combat Scenarios” – 2025 3rd International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings), Mt Pleasant, MI, USA, 2025, pp. 1-7. doi: 10.1109/AIBThings66987.2025.11296222
L. Zhen, M. Li, C. Chakraborty, J. Jiang, Ashok Polavarapu, and F. Alqahtani, “A Lightweight Transformer-Based Collision Detection and Load Estimation Scheme for Massive Random Access in 6G Satellite-Ground Integrated Vehicular Networks” in IEEE Transactions on Intelligent Transportation Systems. doi: 10.1109/TITS.2025.3527073
Chen, C. Chakraborty, Ashok Polavarapu, Q. Yuning, Zhao. Q, Alfarraj. O , and Yu, “A Robust Aggregation of Federated Large Language Models for Multimodal Knowledge Discovery in Computational Social Systems” in IEEE Transactions on Computational Social Systems. doi: 10.1109/TCSS.2025.3575623
SK Thota, Kumari Gubbala, Ashok Polavarapu, Vikram Narayandas, and Dr. Manisha Guduri, “Adversarial Training with Attention-Guided DCGAN for Robust Lung Segmentation in Medical Imaging” 2025 IEEE Region 10 Symposium (TENSYMP), Christchurch, New Zealand, 2025, pp. 1-6. doi: 10.1109/TENSYMP63728.2025.11179918
Ashok Polavarapu, Dr. Manisha Guduri, Ardian Kelmendi, and Dr. Nabih Jaber, “A Novel Hybrid Segmentation Approach for Cardiovascular Disease Prediction Using Gray Slope Correlation and Active Contour Models” 2025 IEEE Region 10 Symposium (TENSYMP), Christchurch, New Zealand, 2025, pp. 1-7. doi: 10.1109/TENSYMP63728.2025.11179920
2024
2024
Synthetic data for Naval Combats Using Generative Adversarial Networks – NAML Conference 2024(Presented)
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