Washington University in St. Louis,
School of Engineering,
Department of Computer Science and Engineering and Division of Computational & Data Sciences,
Theoretical Computer Science and
Machine Learning & Artificial
Spring 20: I am teaching CSE 347.
Check out the new Division of Computational and Data Sciences, a doctoral program for research that uses computational and data-driven methods to advance knowledge in a variety of disciplines in the social and behavioral sciences. Please follow the link for more information.
My work primarily concerns theoretical approaches to artificial intelligence, founded on the theory of algorithms and computational complexity. In particular, I have worked on algorithms for integrated learning and reasoning (e.g., in common sense reasoning), a topic on which I recently gave a tutorial at AAAI-18 with Loizos Michael. Previously, I worked on a theory of communication in the absence of standards (introductions available in three lengths, short, medium, and long). I am also interested in theoretical computer science more broadly construed.
I am currently supported by NSF awards IIS-1908287 (NSF-BSF, in collaboration with Roni Stern) and CCF-1718380. Previously, I was supported by a 2015 AFOSR Young Investigator Award.
I graduated from MIT under the supervision of Madhu Sudan in September 2010; subsequently, I worked as a postdoc under the supervision of Leslie Valiant at Harvard until joining Washington University in Fall 2014. I had also remained (jointly) affiliated with CSAIL as a postdoc with the Center for Science of Information through Summer 2012. In a past life, I was an undergraduate at Carnegie Mellon University, and had the privilege of working with Manuel Blum, which proved to be every bit as awesome as one could imagine.
My thesis on Universal Semantic Communication is available on DSpace. (A revised version is published by Springer.)
Current Ph.D. students: Golnoosh Dehghanpoor, Zihao Deng, Hai Le
Other students I have supervised
CSE 347, Analysis of Algorithms Spring 17, Fall 17, Spring 19
CSE 513T, Theory of Artificial Intelligence and Machine Learning: Spring 15, Fall 16, Spring 18
CSE 519T, Advanced Machine Learning: Fall 19
CSE 544T, Special Topics in Computer Science Theory: Fall 19
CSE 547T, Formal Languages and Automata: Fall 15
CSE 582T, Computational Complexity: Fall 14
Seminars: CSE Colloquium, DSS, MLunch