Nishchal K. Verma, Ph.D.

Smt. Lata and K.G. Karandikar Faculty Chair Professor

Professor, Department of Electrical Engineering,
Indian Institute of Technology Kanpur, India
Mailing Address: 607, Engineering Sciences Building-2,
Indian Institute of Technology Kanpur, Kanpur, India - 208016
Email: [email protected]
Phone: +91 512-259-6524

Biography

Dr. Nishchal Kumar Verma is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur. He has received several awards, including the Smt. Lata and K.G. Karandikar Faculty Chair Professor (2024), the Teaching Excellence (2024), the prestigious research fellowship from UNEC, Azerbaijan (2023), research fellowship from University of Tennessee, Memphis, USA (2022, 2010) and the Devendra Shukla Young Faculty Research Fellowship (2013). Dr. Verma specializes in the theoretical developments of Artificial Intelligence, Machine Learning, and Deep Learning, applying these concepts to Electrical Engineering and various interdisciplinary fields. His research areas include Large Language Models, Intelligent Instrumentation, Control, Automation, Computer Vision, Prognosis and Health Management of Machines, Bioinformatics, and Cyber-Physical Systems, among others.
Dr. Verma and his team have developed several AI-based technologies for The BOEING Company, USA, and organized numerous national and international workshops, conferences, seminars, brain storming sessions and short-term courses. He has published over 270 research papers in reputable peer-reviewed journals and conferences and has authored, co-authored, or edited six books. He has successfully completed a significant number of research projects funded by various agencies, including The BOEING Company, DST, DRDO, MHRD, MeitY, CSIR, IIT Kanpur, MCIT, SFTIG, and VTOL etc. With over 20 years of experience in the fields of Artificial Intelligence and Machine Learning, Dr. Verma serves as an Associate Editor for key publications, including IEEE Transactions on Artificial Intelligence (2020-2024), IEEE Transactions on Neural Networks and Learning Systems (2019-2024), and IEEE Computational Intelligence Magazine (2015-2020).

Research Focus: Artificial Intelligence, Machine Learning, Deep Learning, Large Language Models (LLMs), Condition Based Monitoring/ Prognosis and Health Management of UGV and Rotating Machines, Fuzzy Systems Modelling & Control, Industrial Automation and Control, Computer Vision, Soft-Computing, and Internet of Things/ Cyber-Physical Systems.

I am actively seeking highly motivated students who are passionate about advancing research in Artificial Intelligence (AI) and its interdisciplinary applications. My work spans diverse areas, including but not limited to machine learning, deep learning, computer vision, prognosis and health management, bioinformatics, cyber-physical systems, complex and highly non-linear systems modeling, clustering, and classifications. If you are driven to explore these cutting-edge fields and contribute to impactful research, I encourage you to reach out and discuss potential opportunities for collaboration. Please email your detailed CV to [email protected].