Qualification → PhD
Area of Interest →
Dynamical systems & control: Modelling forced or unforced evolution in a state space & establishing its stability and control. Theoretical & data driven system dynamics in statistical learning framework, computing system dynamics, stability & control to estimate perception, prediction & planning in an autonomous control system.
Statistical learning: Designing a predictive function in statistical learning framework with discriminative modelling (e.g. regression) or generative modelling (e.g. multi-modality with CVAE) by minimizing a suitable loss function. Transforming a learning problem as an optimization problem.
Optimization: first order & second order adaptive descent algorithms, interior point method for convex problems. Convexification or relaxation or breaking symmetry or introducing uncertainty in non-convex problems & transforming geometrical or physical intuition of the problem into a scalable optimization algorithm.
Field of Interest → Learning dynamical systems and control, autonomous control systems