Past Research
Sensorimotor Control for Locomotion
We constructed a bio-inspired framework using coupled oscillator feedback particle filter and Q-learning to obtain the optimal control of periodic locomotion gaits. The framework is under the partially observed settings and does not require knowledge of the explicit form of the dynamics or the observation model.
Neural Rhythms
Oscillators, synchronization, and signal processing.
The goal of our research is to develop neuro-morphic architectures for implementing Bayes rule. One such architecture is the coupled oscillator feedback particle filter model.
Mean Field Games
The objective here is to explore phase transition and self organization in large population dynamic systems. A central goal of this research is the largely classical question of emergent behavior in such dynamical systems.