Quantum Computing: A Shift from Bits to Qubits / Studies in Computational Intelligence Bd.1085 (PDF)

Committee of many international/national conferences. She is also Member of many international and national bodies like CSI, IAENG, IDES, SDIWC, etc.
Dr. Neeraj Kumar Singh is an Associate Professor in computer science at INPT-ENSEEIHT and member of the ACADIE team at IRIT. Before joining INPT, Dr. Singh worked as a research fellow and team leader at the Centre for Software Certification (McSCert), McMaster University, Canada. He worked as a research associate in the Department of Computer Science at University of York, UK. He also worked as a research scientist at the INRIA Nancy Grand Est Centre, France, where he has received his Ph.D. in computer science. He leads his research in the area of theory and practice of rigorous software engineering and formal methods to design and implementation of safe, secure and dependable critical systems. He has authored/edited two books and one conference proceeding. He published more than 80+ peer-reviewed researcharticles in well-known journals, books and international conferences. He has been involved in many scientific activities. He is also involved in several research projects on formal methods and system engineering as project leader and as scientific coordinator.
Dr. Kanishka Tyagi is a senior machine learning scientist at Aptiv advances engineering center, California. He received his Bachelor's Degree in Electrical Engineering in 2008 from Pantnagar, India. Later he worked as a Research Associate at the Department of Electrical Engineering, Indian Institute of Technology, Kanpur, with Dr. P. K. Kalra. He received his Master's and Doctoral degree with Dr. Michael Manry in the Department of Electrical Engineering at The University of Texas at Arlington in 2012 and 2017. Prior to Aptiv, he worked at Siemens research, interned in machine learning groups at The MathWorks and Google Research. He has worked as a visiting researcher at Ajou University and Seoul NationalUniversity. His research interests are radar machine learning, neural networks and hardware machine learning. He received the 2007 and 2011 IEEE CIS Outstanding Student Paper Travel Grant Award and 2013 IEEE CIS Walter Karplus Summer Research Grant award. Dr. Tyagi has taught four undergraduate/graduate courses on Big Data, soft computing and machine learning. Dr. Tyagi is a IEEE senior member, member of IEEE-CIS industrial-academic committee and IEEE standards committee on Explainable AI. He currently serves as an associate editor for IEEE Transaction on Neural Network and Learning Systems and IEEE Transactions on Artificial Intelligence. Dr. Tyagi has published over 30+ papers and filed 17 U.S. patents and trade secrets.