His research focuses on combining Bayesian framework with Deep Learning models. His group is also actively involved in developing more efficient algorithms for diffusion models, studying the properties of loss landscape in deep neural networks, building scalable tools for stochastic optimization, application of tensor decomposition methods to large-scale Machine Learning, improving conditional text generation models, etc.