PhD Thesis on 'Reconstruction, Analysis and Synthesis of Collective Motion', supervised by Prof. P. S. Krishnaprasad, developed novel data smoothing algorithms by exploiting techniques from optimal control theory, investigated feedback mechanisms governing collective behavior in biological settings, and leveraged the insight to design algorithms for collaborative autonomy
Research Experience
- Staff Scientist at Siemens Technology
- Associate Research Scholar and Lecturer at Princeton University, with research focused on nonlinear dynamics and control in complex, multi-agent systems and mathematical analysis of cognitive architectures, designed and taught a Graduate Course on Nonlinear Control, closely collaborated with Prof. Naomi E. Leonard and Prof. Jonathan Cohen
Education
- PhD (Feb 2015) - Electrical Engineering, University of Maryland, College Park, MD, USA, Advisor: Prof. P. S. Krishnaprasad
- M.Tech (Aug 2008) - Systems and Control Engineering, IIT Bombay, Mumbai, India
- B.E. (Jul 2006) - Electrical Engineering, Jadavpur University, Kolkata, India
Background
Research interests include physics-informed machine learning and its industrial applications, ML theory, nonlinear dynamics and control, networked multi-agent systems, and collaborative autonomy. Currently a Staff Scientist at Siemens Technology, focusing on physics-informed machine learning and its application in control and simulation problems.