Assistant Professor, Computer Science & Engineering
- Ph.D., Computer Science, University of Texas at Austin
- B.S., Mathematics and Computer Science, Georgia Institute of Technology
Anup Rao concentrates his research in theoretical computer science. His past work has focused on the study of pseudo randomness, lower bounds and approximation algorithms, efficient ways to reduce the dependence of computer science solutions on pure randomness, and on improving understanding of optimization problems for which it is hard to approximate answers.
Rao’s theoretical research has achieved success in answering the questions “To what extent is the use of randomness necessary to computer science?” and “How can we amplify the hardness of computational problems?” Such questions can sometimes lead to strange and unexpected discoveries; for example, a recent sequence of papers that he co-authored led to the discovery of the most efficient shape for soap bubbles.
Prior to joining UW, Rao was a postdoctoral researcher at the Institute for Advanced Study in Princeton, New Jersey, and at Princeton University. His awards include a Dean’s Excellence Award and MCD Fellowship, both at the University of Texas at Austin, and a President’s Award for Undergraduate Research at the Georgia Institute of Technology.