Associate Professor, School of Computer Science
|Professor Peng’s research is broadly in the design and analysis of fast algorithms for solving fundamental computational problems, including graph algorithms, dynamic algorithms, and linear algebraic algorithms. His representative results include linear systems solvers, max-flow/min-cut algorithms, and time/space efficient data structures for matchings, resistances, and matrices.
Over the past two decades, there is a movement starting in theoretical computer science to design faster algorithms for combinatorial problems using continuous methods. These efforts started with the study of faster solvers for graph structured linear systems, and led to new understandings of algorithmic tools such as sparsification, vertex/variable elimination, and iterative convergences. By taking approaches motivated by data structures and high-performance computing, Professor Peng and collaborators gave new ways of integrating discrete primitives with approximations. Such work led to improvements on multiple well-studied problems, and are starting to find their way into practice via parallel computing and network science.
Professor Peng teaches undergraduate algorithms courses on algorithms and complexity, and is active in his mentoring work of research-oriented students. He spends much time in outreach activities for high school students and undergraduate students, especially in the programming contest community. When not thinking about problems, Professor Peng enjoys biking, baseball, swimming, road trips, and e-sports.