Combining Visual Intelligence and Federated Learning in Smart Healthcare

Smart devices in healthcare can interact with the environment by gathering, processing, interpreting, storing, and retrieving information originated from sensors, neuromorphic analog circuits, robots, and other data retrieving sources through explainable AI, Internet of Things, gestural technology, and federated learning. These systems can utilize visual languages to improve communication with people in real-life scenarios, such as intelligent devices which recognize patterns. Such languages, combined with intelligent, experience-based, healthcare systems, fall in the area of visual intelligence, empowering people to understand how machines process the data smart healthcare devices. The combination of smart healthcare and visual intelligence with federated learning may give rise to new applications in fields as diverse as healthcare, education, marketing, gaming, and automation. Combining Visual Intelligence and Federated Learning in Smart Healthcare explores research areas that connect visual information processing with intelligence, federated learning, and the Internet of Things, promoting their integration and exciting new developments. It examines theories, practices, and experiences in the field of smart healthcare for visual intelligence with federated learning. This book covers topics such as artificial intelligence, predictive analytics, and smart technology, and is a useful resource for medical professionals, business owners, healthcare workers, computer engineers, data scientists, academicians, and researchers.

Dr. Manisha Guduri is currently an Assistant Professor (Tenure Track) at Lawrence Technological University. She is the author/ coauthor of more than 80 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 received two patent grants. She is a senior member of IEEE, USA. She is also a member of various IEEE Societies - IEEE YP, IEEE WiE, Circuits and Systems, Computer Society, Sensor Council, etc. She is IEEE Lafayette Section Chair for 2025. She is an IEEE USA Awards and Recognition Committee Member at Large. She is nominated for the Associate Editor - DM role of IEEE JETCAS for 2026. 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.

Dr. Chinmay Chakraborty, received a Post-doctoral fellowship at the Federal University of Piauí, Brazil, and also visited the University of Malta in Europe and Chongqing Tech. & Business Univ., China. He is an Associate Professor of KIIT-DU, India. His main research interests include the Internet of Medical Things, AI-ML, Communication & Computing, m-Health/e-health, and Medical Imaging. Dr. Chakraborty has a strong publication record with over 250 articles in peer-reviewed international journals, conferences, and book chapters. He has secured a top 2% position among global scientists by Stanford University in both 2021-24. He has also received a Marie Skłodowska-Curie Actions Europe Fellowship Grant, Horizon 2023, and has been nominated as a "Prominent Young Researcher" at the INAE, SERB, India. He Received Prize Ideation Startup Competition at the ANRF (SERB) - INAE Conclave, 2025. He received BIT BITFAA'24 award, 2024 and nominated as AICTE-Distinguished Professional, 2025.

Prof. Martin Margala , PhD joined the School of Computing and Informatics as Professor and Director in August 2021. Before joining UL Lafayette, from September 2011 to July 2021, Dr. Margala was Professor and Chair of the Electrical and Computer Engineering Department at the University of Massachusetts Lowell and a Co-Director of the Center for Smart Cyber-Physical Systems (SCyPS). He received his PhD degree in Electrical and Computer Engineering from the University of Alberta, Canada (#61 in Global Ranking in North America region; #13 in Global subject specific ranking Electrical and Electronic Engineering in North America region USNews) in the spring of 1998. He is a senior member of ACM, IEEE, and SPIE with more than 50 journal and 200 peer reviewed conference publications in the areas of Design for Testability for Energy Efficient Architectures and Systems, High-Performance Reliable Low-Power Architectures and Reconfigurable Secure Architectures and Systems. Dr. Margala has directed 22 PhD students and 19 MS students, many of whom now hold leading positions in academia and industry. He has served on numerous program committees of international conferences and on workgroups (such as the International Technology Roadmap for Semiconductors) that have a great impact on the future direction of academia and industry.