I completed my PhD in Computing and Information Sciences from Rochester Institute of Technology under advisement of Prof. Linwei Wang.
I am generally interested in computational and algorithmic aspects of learning. I have worked on 1) probabilistic models and Bayesian inference, 2) generative modeling and semi/self/un-supervised learning, and 3) generalization and robust/reliable estimation. I have applied these ideas in the context of computer vision/ video analysis problems, medical imaging and biomedical signals. My current research projects include score based generative models, energy based models, representation learning in videos, kernel methods etc. In my PhD thesis, I focused on learning and generalization in the context of reconstructing cardiac electrophysiological signals.
PhD in Computing and Information Science, 2020
Rochester Institute of Technology
BE in Electronics and Communication Engineering, 2012
Institute of Engineering
Can we learn meaningful representation from real world videos or biomedical signals ?
How to understand and improve generalization and robustness in deep networks?
Apply probabilistic modeling, deep generative modeling and inference to solve inverse problem.