Through my research at CSM, I am working on developing a robust motion planner that can provide an accurate and efficient infeasibility reasoning during path planning using the topology of the robot's configuration space.
I graduated with a Ph.D. in Computer Science from the University at Albany, SUNY. My research integrates concepts from Computational Geometry, Applied Mathematics, and Machine Learning. My work focuses on the robot motion planning problem and utilizes Topological Data Analysis (TDA) methods to optimize motion planning by leveraging environmental properties. The developed topology approach also extends its applications to computational biology problems, particularly in identifying optimal binding positions for protein-ligand or protein-protein interactions.