Ashwin Pananjady


PhD Student
Department of Electrical Engineering and Computer Science
University of California, Berkeley

Contact: Berkeley Laboratory for Information and System Sciences, 264 Cory Hall

About me

I am a fourth year graduate student in the EECS Department at UC Berkeley, advised by Martin Wainwright and Thomas Courtade. My thesis committee members are Martin Wainwright, Thomas Courtade, Michael Jordan, and Adityanand Guntuboyina. My interests are broadly in statistical machine learning, information theory and optimization, and I am particularly interested in the conceptual and theoretical underpinnings of models and algorithms. Specific topics that I like thinking about include latent parameter estimation, distributed optimization, functional inequalities, missing data, structured matrix completion, reinforcement learning, and deep learning. I spent the summer of 2017 at Microsoft Research Redmond, where I worked with Denny Zhou and Lihong Li in the deep learning and reinforcement learning groups.

Before coming to Berkeley, I graduated with a B.Tech in Electrical Engineering from the Indian Institute of Technology (IIT) Madras, and was fortunate to have worked with Rahul Vaze, Sounaka Mishra and Andrew Thangaraj during my bachelor’s degree.