Sanket Sanjay Diwale
Mr. Diwale started his Doctoral studies in EPFL, Switzerland at the Doctoral school for Electrical Engineering in October 2013. Prior to that he obtained his Bachelors and Masters in Electrical Engineering from the Indian Institute of Technology, Bombay. During his doctoral studies, he worked on nonlinear adaptive control, optimal control and receding horizon approximations of these methods for control of dynamical systems. He worked on adjoint methods for machine learning and optimal control to provide a unified framework for numerical methods for learning, optimal control and receding horizon control schemes for both stochastic and deterministic dynamical systems. His research interests lie in stability analysis of such schemes for stochastic and adaptive dynamical systems and in closing the loop of data driven modelling with online and adaptive control schemes with safety constraints. These methods having applications in mathematical finance and policy making for risk management, portfolio optimisation problems and in engineering applications for control design and data driven synthesis of optimal control schemes motivate him to look further into these problems. He also worked as a researcher during an internship at Siemens Industry Software, Belgium from August 2017 - February 2018, during which time he worked on Manifold Learning and Model Predictive Control for obstacle avoidance and control for autonomous driving vehicles.