Welcome

Piyush Rai I'm an associate professor in Computer Science & Engineering at Indian Institute of Technology, Kanpur. Before this (reverse chronologically), I was a research faculty in Electrical and Computer Engineering, at Duke University, a post-doctoral fellow in Statistics and Computer Science at UT Austin, and a Ph.D. student in School of Computing at University of Utah. I work in the area of machine learning and Bayesian statistics. My research is primarily on probabilistic/generative modeling and understanding of massive and complex data.

My students and I focus on designing probabilistic generative models and efficient optimization/inference algorithms that can learn compact and interpretable latent structures and feature representations from such data, and leverage these to better understand/summarize the data, generate data with controllable properties, and make better predictions/decisions, especially in the face of data/model uncertainty. We also work on designing machine learning models and algorithms that can work well in resource-constrained settings (e.g., scarce training data or under limited compute/storage).

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