Suqi Liu

Department of Biomedical Informatics

Harvard Medical School

Email: suqil at med dot harvard dot edu

Office: Countway Library

I am a Postdoctoral Research Fellow in the Department of Biomedical Informatics at Harvard Medical School working under Professor Tianxi Cai. I received my Ph.D. from Princeton University advised by Professor Miklos Racz.

My research interests lie broadly at the intersection of probability, statistics, and combinatorics. Specifically, I study random graphs with latent geometric structure with application to biomedical networks.

Previously, I was a graduate student at UC San Diego advised by Professor Lawrence Saul, co-advised by Professor Geoffrey Voelker and Professor Stefan Savage. I completed my undergraduate study at Tsinghua University where my thesis adviser was Professor Jun Zhu.

I did internships at Google working on Google Knowledge Graph and Google Ads in the Bay Area during the summers of 2016 and 2018. I also interned at Microsoft Research Asia from April to November 2012.


  • Ph.D. in Operations Research and Financial Engineering, Princeton University, 2016–2022.

  • M.S. in Computer Science, University of California, San Diego, 2013–2016.

  • B.S. in Mathematics and Physics, Tsinghua University, 2009–2013.



Conference and workshop papers


  • Phase transitions in soft random geometric graphs. Graduate Student Seminar, PACM, Princeton, March 15, 2022.

  • Phase transitions in soft random geometric graphs. Stochastics Seminar, School of Mathematics, Georgia Tech, January 13, 2022.

  • A probabilistic view of latent space graphs and phase transitions. Northeast Probability Seminar, November 18, 2021. [video] [slides]

  • Phase transition in noisy high-dimensional random geometric graphs. Columbia–Princeton Probability Day, May 7, 2021. [video] [slides]

  • Learning to parse WHOIS records. Internet Measurement Conference, Oct 30, 2015. [slides]


  • Assistant in Instruction, ORF 309 (Probability and Stochastic Systems), Princeton, Spring 2022.

  • Assistant in Instruction, ORF 526 (Probability Theory), Princeton, Fall 2018, Fall 2019, Fall 2020.

  • Assistant in Instruction, ORF 387 (Networks), Princeton, Spring 2020, Spring 2021.

  • Assistant in Instruction, ORF 350 (Analysis of Big Data), Princeton, Fall 2017, Spring 2019.

  • Assistant in Instruction, ORF 307 (Optimization), Princeton, Spring 2018.

  • Teaching Assistant, CSE 250A (Principles of Artificial Intelligence), UCSD, Spring 2016.

  • Teaching Assistant, CSE 150A (Introduction to Artificial Intelligence), UCSD, Winter 2016.