My research focuses on combinatorial algorithms and computational methods for data analysis, especially data that can be modeled by a graph or network. This combines interests in CS theory, computational science, discrete mathematics, machine learning, and various data science applications.
New and Events
- January 6, 2023. Our research on “Combinatorial Characterizations and Impossibilities for Higher-order Homophily” (joint with Austin Benson and Jon Kleinberg) has been published in Science Advances. I had a chance to discuss some of this research as part of a recent article in the Communications of the ACM.
- January 5, 2023. I am honored to have been selected for the SIAM SIAG/ACDA Early Career Prize. I look forward to giving a talk on my research at the 2023 ACDA Conference in Seattle, Washington, May 31-June 2.
- August 4, 2022. Our research on “Hypergraph Cuts with General Splitting Functions” (joint with Austin Benson and Jon Kleinberg) is now published in SIAM Review. Here is a summary by the section editor. My co-author Austin Benson talks a bit more about this research in a Quanta magazine article.
- April 11, 2022. I am honored to be awarded the 2022 Texas A&M Institute of Data Science Career Initiation Fellowship!
See my news page for more information about news and recent events.
Graph Algorithms, Network Science, Combinatorial Optimization, Matrix Computations, Data Science.
- Hypergraph algorithms for higher-order data analysis
- Flow-based methods for community detection
- Approximation algorithms for correlation clustering