Phil Chodrow

Applied math and data science @UCLA (he/him/his)



I am a Hedrick Visiting Assistant Adjunct Professor in the Department of Mathematics at UCLA, mentored by Mason Porter. My interests include network science, nonlinear dynamics, applied probability, and machine learning. In my research, I build principled tools for studying the structure and dynamics of networked systems. Recent projects include models of random graphs and hypergraphs; dynamics of adaptive networks; inference in generative network models; and techniques for clustering higher-order network data.

I am a passionate educator, and teach subjects ranging from applied probability to network science to computer programming. I am enthusiastic about evidence-based, inclusive teaching; project-based learning; and a human-centered approach to creative, quantitative problem-solving. I am also a Partner and Affiliated Data Scientist at QSIDE, the Institute for the Quantitative Study of Inclusion, Diversity, and Equity. At QSIDE, I support projects that build quantitative insight about disparity in the United States, and mentor undergraduates on modern tools and practices for data science.

I did my PhD at MIT’s Operations Research Center under the mentorship of Marta Gonz├ílez and Patrick Jaillet. My research at MIT was supported by the NSF Graduate Research Fellowship.


  • January 26th, 2020: New preprint! “Hypergraph clustering: from blockmodels to modularity” with Nate Veldt and Austin Benson. arXiv link
  • October 28th, 2020: “Moments of uniform random multigraphs with fixed degree sequences is now published in the SIAM Journal on Mathematics of Data Science. You can read the full text.
  • Aug. 4th, 2020: “Configuration models of random hypergraphs” is published in the Journal of Complex Networks. You can read the full text.
  • July 10th, 2020: New preprint! “Emergence of hierarchy in networked endorsement dynamics” with Nicole Eikmeier, Mari Kawakatsu, and Dan Larremore. arXiv link.
  • July 9th-10th, 2020: Contributed (virtual) talk on multigraphs with fixed degree sequences at the SIAM Workshop on Network Science (with slides). Additionally, Nicole Eikmeier will present our recent work with Mari Kawakatsu and Dan Larremore on emergent hierarchies in networks.
  • April 1st-3rd, 2020: I (virtually) attended the Northeastern Regional Complex Systems Conference (NERCCS), where I gave a talk (with slides) on random graphs and a poster on generative models of hierarchy in networks. Update: best-poster award with Nicole Eikmeier, Mari Kawakatsu, and Dan Larremore!

Upcoming talks