Dana Randall has established an exciting program in a new field of interdisciplinary work bridging statistical physics and computer science. Her research is in discrete mathematics and theoretical computer science, and involves designing Markov chain Monte Carlo algorithms for counting and sampling from large sets of combinatorial structures. Randall is doing pioneering work in providing fast polynomial time algorithms with rigorous and provable performance guarantees. Her work brings together intuition and techniques from theoretical computer science and statistical physics, and is truly interdisciplinary in nature, with rich potential for further important and groundbreaking contributions.
- Counting Complexity and Phase Transitions, Spring 2016. Visiting Scientist.