Federated Intelligence in Medicine

Dr. Manisha Guduri is currently a Full Time Instructor at the University of Louisiana at Lafayette, USA. She is the author/ coauthor of more than 71 research papers in reputed journals, book chapters, and international conferences. Her research interests include Artificial Intelligence, Biomedical Applications, VLSI/CAD design. She is currently working on VLSI and AI in the biomedical field. She published 5 patents out of which 2 are under FER. She received one patent grant. She is the reviewer of IEEE TVLSI, Microelectronics Journal, IET digital circuits, IEEE Journal of Biomedical and Health Informatics, etc. She has one on-going funded project from the Department of Science and Technology. She is a senior member of IEEE, USA. She is also currently member of various IEEE Societies such as IEEE Young Professionals, IEEE Women in Engineering, Circuits and Systems, Computer Society, Sensor Council, etc. She is appointed as IEEE WiE CASS representative for 2023 & 2024. She is IEEE WiE DL program Coordinator and IEEE Computer Society Lafayette section Vice Chair for 2024. She has delivered more than 35 invited talk/tutorial speech/expert talk in various platforms like International Conference /technical programs. She has organized 10 international conferences under different roles.Chinmay Chakraborty is an Associate Professor and Head, Centre of Innovation & Research (COIR) in Medical Technology, KIIT Deemed to be University, India. His main research interests include the Internet of Medical Things, Medical technology, m-Health/e-health, and AI-ML. He is an Editorial Board Member of various different journals and conferences. Dr. Nabih Jaber is an Associate Professor and Chair of the Department of Electrical and Computer Engineering. His research interests include Intelligent Transportation Systems (ITS), wireless communications, coding and information theory, Dedicated Short Range Communications (DSRC) vehicular systems, smart grid power line communications, sensor networks, and Advanced Driver Assistance Systems/Autonomous Vehicles (ADAS/AV). He is also engaged in test-bed implementations and the design of innovative simulation systems.Dr. Jaber actively contributes to the teaching community, having obtained the University Teaching Certification (UTC) from SEDA, which promotes innovation and best practices in higher education. He has also earned certificates in Leading Effective Discussions, Instructional Skills, Teaching Dossier, and Millennial Students: Myths and Realities.He currently directs the Innovative Smart Wireless Networking Lab (ISWiNLab) and serves as the IEEE Student Branch Advisor at LTU. Additionally, he has previously served as Director of the Master of Science in Electrical and Computer Engineering (MSECE) Graduate Program.Keping Yu received the M.E. and Ph.D. degrees from the Graduate School of Global Information and Telecommunication Studies, Waseda University, Tokyo, Japan, in 2012 and 2016, respectively. He was a Research Associate, Junior Researcher, Researcher with the Global Information and Telecommunication Institute, Waseda University, from 2015 to 2019, 2019 to 2020, 2020 to 2022, respectively. He is currently an associate professor at Hosei University and a visiting scientist at the RIKEN Center for Advanced Intelligence Project, Japan. Dr. Yu has hosted and participated in more than ten projects, is involved in many standardization activities organized by ITU-T and ICNRG of IRTF, and has contributed to ITU-T Standards Y.3071 and Supplement 35. He received the IEEE Outstanding Leadership Award from IEEE BigDataSE 2021, the Best Paper Award from IEEE Consumer Electronics Magazine Award 2022 (1st Place Winner), IEEE ICFTIC 2021, ITU Kaleidoscope 2020, the Student Presentation Award from JSST 2014. He has authored 100+ publications including papers in prestigious journal/conferences such as the IEEE WCM, CM, NetMag, IoTJ, TFS, TII, T-ITS, TVT, TMC, JBHI, TR, TCOM, TNSM, TIM, TNSE, TGCN, TCSS, CEM, IOTM, ICC, GLOBECOM etc. He is an Associate Editor of IEEE Open Journal of Vehicular Technology, Journal of Intelligent Manufacturing, Journal of Circuits, Systems and Computers. He has been a Guest Editor for more than 20 journals such as IEEE TCSS. He served as general co-chair and publicity co-chair of the IEEE VTC2020-Spring 1st EBTSRA workshop, general co-chair of IEEE ICCC2020 2nd EBTSRA workshop, general co-chair of IEEE TrustCom2021 3nd EBTSRA workshop, session chair of IEEE ICCC2020, ITU Kaleidoscope 2016. His research interests include smart grids, information-centric networking, the Internet of Things, artificial intelligence, blockchain, and information security.

• 1. Secure Cloud-Integrated Healthcare Robotic System for Real-Time Medical Data Sharing Using Enhanced Discrete Domain Adaptation Hopfield Neural Network2. Intelligent Robotics and Collaborative Systems: Integrating Artificial Intelligence, Medical Robotics, Federated Learning, and Industry 5.03. Parallel Adaptive Transformer Coupling Convolutional Neural Network Framework for Secure Communication and Data Integrity in Medical Robotics4. An Intelligent Federated Learning Architecture for Remote Robotic Surgery Using Optimized Directed Acyclic Generalized Simplicial Graph Neural Network5. Conceptual Foundations of Generative Artificial Intelligence and Federated Learning in Healthcare6. Secure Collaborative AI in Healthcare Through Privacy-Preserving Federated Learning Across Medical Institutions7. Federated Authentication Framework for Secure and Privacy-Preserving Medical IoT8. A Novel Approach for Gastrointestinal Endoscopy Image Classification through Enhanced Multiview Feature Fusion and Light Weight Models9. Enhanced Speaker Diarization and Gender Identification Using CNN-LSTM Hybrid Framework for Secure Clinical Communication in AI-Driven Healthcare Robotics10. A deep learning-based Autonomous Control in Healthcare Robotic Applications for COVID-19 detection and assistance11. Multiple-class Fine-Tuned SAM for Enhanced Bariatric Surgery Image Segmentation12. Human Robot Interaction Using Federated Learning in Healthcare13. A Federated Multimodal Learning Approach with Adaptive Aggregation for Privacy-Preserving Cardiac Diagnosis14. FedBioTwin-Rehab: Biomechanics-Regularized Personalized Federated Digital Twins for PrivacyPreserving Wearable Rehabilitation in Knee Osteoarthritis and Freezing of Gait in Parkinson's Disease15. Medical imaging robotics integration with federated learning for privacy-preserving healthcare systems16. Robotic Agentic AI for Treatment Process Automation: Towards Patient-centered Healthcare Ecosystem17. Federated Generative AI on Chest X-Ray Images: Privacy-Preserving Synthetic Data Generation and Clinical Decision Support18. An Exploration of Generative AI and Federated Learning for Secure Early Diagnosis of Mild Cognitive Impairment using Neuroimaging19. An Intelligent Breast Cancer Detection Framework Using Stereoscopic Scalable Kolmogorov-Arnold Quantum Convolutional Neural Network Optimized with Bobcat Algorithm for Healthcare Data Analytics20. A Federated Agentic Artificial Intelligence Framework for Complex Decision-Making in Heart Disease Prediction