My research interest is using methods from mathematics and machine learning to solve problems related statistical physics. I am currently working on developing novel methods to map topography of configuration space by combining measure theory, functional analysis and homology theory with statistical mechanics. Developing such methods helps us to locate the global and local minimas of energy and in the process help us understand different pathways a reaction will take in the configuration space.