Suman Lata Tripathi completed her PhD in the area of microelectronics and VLSI from MNNIT, Allahabad. She was also a remote post-doc researcher at Nottingham Trent University, London, UK in 2022. She is a Professor at Lovely Professional University with more than 19 years of experience in academics. She has published more than 89 research papers in refereed journals and conferences. She has also published 13 Indian patents and 2 copyrights. She has organized several workshops, summer internships, and expert lectures for students. She has worked as a session chair, conference steering committee member, editorial board member, and peer reviewer in international/national conferences. She received the “Research Excellence Award” in 2019 and “Research Appreciation Award” in 2020, 2021 at Lovely Professional University, India. She also received funded projects from SERB DST under the scheme TARE in the area of Microelectronics devices. She has edited or authored more than 15 books in different areas of Electronics and electrical engineering. Her areas of expertise includes microelectronics device modeling and characterization, low power VLSI circuit design, VLSI design of testing, and advanced FET design for IoT, Embedded System Design, reconfigurable architecture with FPGAs and biomedical applications.Dr. Kolla Bhanu Prakash is a Professor and Research Group Head in the CSE Department, KL University, India. His current research interests include Deep Learning, Data Science, Smart Grids and Image Processing. Valentina Emilia Balas is Full Professor in the Department of Automatics and Applied Software, Faculty of Engineering, at Aurel Vlaicu University of Arad, Romania. She holds a PhD in Applied Electronics and Telecommunications from the Polytechnic University of Timisoara. Her research spans intelligent systems, computational intelligence, applied informatics, and engineering applications. Dr. Balas serves as Editor-in-Chief of International Journal of Advanced Intelligence Paradigms and International Journal of Computational Systems Engineering, and is a member of the editorial boards of several international journals. She is actively involved in the evaluation of national and international research projects and doctoral theses, and contributes to scholarly initiatives that support the advancement of intelligent and computational systems research. Janmenjoy Nayak is an Assistant Professor, P.G. Department of Computer Science, Maharaja Sriram Chandra Bhanja Deo University, Baripada, Odisha, India. He has been a Gold Medallist in Computer Science twice in his career, and has been awarded the “Innovation in Science Pursuit for Inspired Research” (INSPIRE) Research Fellowship from the Department of Science & Technology, Government of India (at both Junior Research Fellow and Senior Research Fellow level) and Best Researcher Award from Jawaharlal Nehru University of Technology, Kakinada, Andhra Pradesh for the academic year 2018–19. He has received many other awards from national and international academic agencies. Dr. Nayak has edited 19 books and 8 special issues on the applications of computational intelligence, soft computing, and pattern recognition, which have been published by Springer and Inderscience. He has published more than 190 refereed articles in various book chapters, conferences, and peer-reviewed journals of Elsevier, Inderscience, Springer, the Institute of Electrical and Electronics Engineers (IEEE), and others. He has also served as a reviewer for more than 100 journals and conferences produced by the IEEE, the Association for Computing Machinery (ACM), Springer, Elsevier, Wiley, and Inderscience. He has 11 years of experience in both teaching and research. Dr. Nayak is a senior member of the IEEE and a life member of societies such as the Soft Computing Research Society (SCRS), the Computer Society of India (CSI India), the Orissa Information Technology Society (OITS), the Orissa Mathematical Society (OMS), and the International Association of Engineers (IAENG), Hong Kong. He has successfully conducted and is associated with 14 internationally renowned series conferences such as ICCIDM, HIS, ARIAM, CIPR, and SCDA. His areas of interest include data mining, nature-inspired algorithms, and soft computing.

• 1. Carbon-Based Electrodes as a Scaffold for the Electrochemical Sensing of Pharmaceuticals: A Special Case of Immunosuppressant Drugs2. Selenium-Based Amorphous Semiconductors and their Biomedical Applications3. Nanodevices in Biomedical Applications4. Analytical Model and Sensitivity Analysis of a Gate Engineered Dielectric Modulated Double Gate MOSFET Based Biosensor5. Design and Development of AlGaN/GaN HEMT for Bio-Sensing Applications for the Detection of Cancers, Tumours and Kidney Malfunctioning6. Preprocessing of the Electrocardiogram Signal for a Patient Parameter Monitoring System7. A Study on Sleep Stage Classification Based on a Single Channel EEG Signal8. Implementation of Ultra Low-Power Electronics for Biomedical Applications9. Sensors and their Application10. ADC and DAC for Biomedical Applications11. A Low Power Reconfigurable ADC for Bioimpedance Monitoring Systems12. Design of a 16-Bit 500 MS/s SAR ADC for Low Power Applications13. Design and Applications of Rail to Rail FC-OTA and Second Generation CCII+ Cells14. The Role of Electronic Filters in Biomedical Applications: A Brief Survey15. Fingerprint Based Smart Medical Emergency First Aid Kit Using IOT16. An Overview to the Dynamics of Telemedicine & Robotics for the Benefit of Mankind17. A LabVIEW-Based Guidance System to Assist in Reading and Analyzing the Traffic Rules Using Raspberry Pi for the Visually Impaired18. An Overview of the Various Medical Devices for Diagnosis, Monitoring and Treatment of Diseases19. Efficient Wireless Power Transfer System for Biomedical Applications20. The Impact of IoT in Biomedical Applications: Part I21. The Impact of IoT in Biomedical Applications: Part II22. A Health Monitoring System23. Real Time Health Monitoring using IoT Sensors24. An E-Health Monitoring System25. Comparative Analysis of Various Supervised Machine Learning Techniques for Diagnosis of COVID 19