About
Appointed Canada CIFAR AI Chair – 2021
Rahul G. Krishnan is an Assistant Professor of Computer Science and Medicine (Laboratory Medicine and Pathobiology) where he holds a Tier II Canada Research Chair in Computational Medicine. He is also a Canada CIFAR AI Chair at the Vector Institute. He works on developing algorithms for causal and probabilistic inference, and applying machine learning to problems in healthcare. Previously, he was a Senior Researcher at Microsoft Research New England.
Awards
- Amazon Research Award, 2023
- Tier II Canada Research Chair in Computational Medicine, 2023
- NeurIPS Top 400 Reviewer, 2019, 2020
- Henning Biermann Award, New York University, 2016
- Pearson International Scholarship, University of Toronto, 2008-2013
Relevant Publications
- End-To-End Causal Effect Estimation from Unstructured Natural Language Data (2024), Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul G Krishnan, Chris J Maddison
- Structured Neural Networks for Density Estimation and Causal Inference, Asic Chen, Ruian Ian Shi, Xiang Gao, Ricardo Baptista, Rahul G Krishnan, NeurIPS 2023
Krishnan, R., Shalit, U., & Sontag, D. (2017, February). Structured inference networks for nonlinear state space models. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 31, No. 1).
Liang, D., Krishnan, R. G., Hoffman, M. D., & Jebara, T. (2018, April). Variational autoencoders for collaborative filtering. In Proceedings of the 2018 World Wide Web Conference (pp. 689-698).
Krishnan, R., Liang, D., & Hoffman, M. (2018, March). On the challenges of learning with inference networks on sparse, high-dimensional data. In International Conference on Artificial Intelligence and Statistics (pp. 143-151). PMLR.