Dr. Rahul Krishnan is an Assistant Professor at the University of Toronto in Computer Science and LMP. He received his PhD from MIT advised by Prof. David Sontag where he was part of the Clinical ML Group. He received a BASc in Computer Engineering at the University of Toronto and an MS from New York University. Rahul was previously a senior researcher at Microsoft Research New England.
He is expanding the Artificial Intelligence education in LMP (alongside Dr. Bo Wang) and has recently launched a new graduate course on Machine Learning for Healthcare
My research lies at the intersection of machine learning and healthcare. I am interested in developing new machine learning methods to automate clinical decision-making.
My current research is focused on the following themes:
- Deep generative modeling: Developing new methods forprobablistic inference and parameter estimation in deep generative models to make them practical tool for uncovering patterns within, and making predictions with complex, multi-modal data.
- Multi-modal models: Developing new learning frameworks for supervised and unsupervised learning that leverage different modalities of data and auxiliary information.
- Insights from observational and interventional data: Developing methods to identify good interventional policies from time-varying observational data.