About

Deepak Sharma is an Associate Professor in the Department of Mechanical Engineering, Indian Institute of Technology Guwahati, India. He obtained his Ph.D. Degree from the Department of Mechanical Engineering, Indian Institute of Technology Kanpur, India, in the area of engineering optimization. Prior to joining IIT Guwahati, he has worked with many international research teams, such as the Department of Business Technology, Helsinki School of Economics, Finland; Department of Computer Science, Univesité de Strasbourg, France; Department of Electrical and Computer Engineering, National University of Singapore, Singapore, and Department of Computer Science and Information Technology, Karlsruhe Institute of Technology, Germany. He was a visiting faculty at Industrial System Engineering, Asian Institute of Technology, Bangkok, Thailand, for a semester in 2015. He was awarded with a best paper presentation award at 2nd International Conference on Future Learning Aspects of Mechanical Engineering in 2021, an NVIDIA Innovation Award in the 21st IEEE International Conference of High-Performance Computing in 2014, DAAD's Research Stays fellowship for summer 2013, best student paper awards in IEEE Congress on Evolutionary Computation conferences in 2007 and 2008. He has continuously been involved in many sponsored and consultancy projects from SERB, DST, and the Ministry of Heavy Industries and Public Enterprises. He is regularly organizing management development programs (MDP) for executes and managers of center and state-level public sector organizations on (1) Production Planning, Inventory Control and Supply Chain Management, (2) Project Management, (3) Inventory and Supply Chain Management, (4) Marketing Management, (5) Artificial Intelligence and Its Implementation in Indian Context. He has published more than 55 research articles in journals and conferences of high repute. His research interests include operations research and management, and optimization and soft computing techniques in management. His teaching interests include operations research, operations management, and optimization methods.