Yin Tat Lee, a co-PI of ADSI, was selected for the 2018 National Science Foundation Faculty Early Career Development (CAREER) program. He will develop faster, more efficient algorithms for solving convex and other optimization problems. The outcome of Lee’s research, which seeks to increase the scientific community’s understanding of the relationship between convex geometry and optimization algorithms and improve upon current techniques drawn from continuous and discrete optimization, will have broad impact across the sciences and beyond.
Recent advances yielding faster algorithms have enabled Lee to break the long-standing running time barriers for specific problems, such as linear programming and maximum flow problems, and to apply optimization techniques to a broader class of problems than was previously feasible. Lee aims to build upon this past work by tackling a set of significant problems in convex geometry and optimization in order to push the state of the art even further.
Beyond the proposed topics, Lee has broad research interests in the applications of convexity. In the coming STOC 2018 (one of the top 2 conferences in theoretical computer science), Lee has a record number of accepted papers (6). Besides convex optimization, these papers are on a breadth of topics including online algorithms, algorithmic convex geometry, asymptotic geometric analysis, operator theory and probability.
See also Lee’s award abstract and coverage on the Allen School news.