I am a research scholar who focusses on Energy Management Strategies (EMS) to reduce energy consumption and emissions. This includes cutting-edge machine learning techniques for State of Charge (SOC) prediction and State of Health (SOH) estimation. My research findings progress other researchers understanding of next generation battery control hardware and software.
I taught a graduate seminar in Machine Learning, an undergraduate course in Battery SOC Estimation, and a crossover course in Battery Management System. Occasionally, I teach Battery Modeling and Controls 101.
I have 15 peer-reviewed scientific articles, 35 patents/patent applications in the area of Powertrain Controls. I have reviewed 99 distinguished journals, conference papers and presentations.