Paras Mandal, Ph.D., SMIEEE
Paras Mandal, Ph.D., SMIEEE
Professor of Electrical & Computer EngineeringDirector, Power & Renewable Energy Systems (PRES) Lab
Dr. Paras Mandal is currently a Professor of Electrical and Computer Engineering (ECE) and the Director of Power & Renewable Energy Systems (PRES) Laboratory within the ECE Department at the University of Texas at El Paso (UTEP), USA. He received his M.E. degree from Asian Institute of Technology, Thailand in August 2002 (under ADB-JSP) and the Ph.D. degree from the University of the Ryukyus, Japan, in September 2005 (under Japanese Government Monbukagakusho scholarship). Dr. Mandal is blessed to have international working experiences (2005–2011) in Japan (Postdoctoral Fellow), South Korea (Research Professor), Australia (Research Fellow), and Canada (Postdoctoral Fellow) before joining the UTEP faculty in the fall of 2011. His research interests include power systems operations and markets, renewable energy integration and forecasting, machine learning applications, and smart grid. He has authored more than 100 scientific articles and proven technical, academic and leadership skill with various awards and honors. He is a recipient of best papers award by IEEE and Young Engineer award from IEEJ. He participates and assumes leadership roles in multiple professional groups within the IEEE Power and Energy Society (PES). He is a Senior Member of IEEE, Secretary of IEEE PES Power & Energy Education Committee (PEEC)–Life Long Learning Subcommittee (LLLSC), Vice-Chair of IEEE PEEC award subcommittee, and Member of various IEEE working groups and subcommittees. Dr. Mandal is a regular reviewer of journals and conferences and, serves as an Editorial Board of the journals and a session chair and panelist in IEEE PES conferences.
The diversity of PRES Lab addresses technological challenges associated with Smart Power Grid and Cyber Physical Systems. Research areas mainly focus on planning and operation of electric energy systems; electricity market; renewable integration and forecasting; demand response; and intelligent system applications in power system.
