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. In my PhD thesis, I focused on learning and generalization in the context of inverse problems. I like to ask deep questions and work towards fundamental understanding, often with the help of theoretical/mathematical analysis. My works are also firmly grounded in medical imaging applications. I believe that theory and application must go hand in hand. Starting with real life applications help us define precise problems, which, in turn, will help us in theoretical pursuit and fundamental understanding.
PhD in Computing and Information Science, 2020
Rochester Institute of Technology
BE in Electronics and Communication Engineering, 2012
Institute of Engineering
How to extract transformation from a dataset and use it for data augmentation?
Apply probabilistic modeling and inference to solve inverse problem.
Apply smoothness based regularization to help semi supervised learning.