Jayadev Acharya, assistant professor of electrical and computer engineering, received the Best Paper Award at the 31st International Conference on Algorithmic Learning Theory (ALT 2020), held in San... Read more about Jayadev Acharya receives Best Paper Award at ALT 2020
I joined Cornell in August 2016 as an Assistant Professor in the school of Electrical and Computer Engineering, after spending two years as a postdoc at MIT. I obtained my Ph.D. from University of California, San Diego, and my B. Tech degree from Indian Institute of Technology, Kharagpur.
I am interested in information theory, algorithmic statistics, and machine learning. In particular, I am interested in understanding the trade-offs between resources (e.g., data, memory, time, etc) for problems in statistical learning. During my graduate work, I worked on compression and statistical estimation, with particular emphasis on problems over large domains.
- Information Theory and Communications
- Statistics and Machine Learning
- Complex Systems, Network Science and Computation
- 2016."Sample-optimal density estimation in nearly-linear time". .
- 2015."Optimal testing of properties of distributions." .
- 2015."The complexity of estimating Rényi entropy." .
- 2015."String reconstruction from substring compositions."29(3): 1340-1371. .
- 2014."Near-optimal-sample estimators for spherical gaussian mixtures." .
Selected Awards and Honors
- MIT Energy Initiative Fellowship(MIT)2014
- Shannon Graduate Fellowship(UCSD)2012
- Jack Keil Wolf Student Paper Award(ISIT)2010
- B.Tech..(Electronics and Communication Engineering),IIT Kharagpur,2007
- M.S.(Electrical and Computer Engineering),University of California, San Diego,2009
- Ph.D.(Electrical and Computer Engineering),University of California, San Diego,2014