Suqi Liu

I am a final year Ph.D. student at Princeton University working with Professor Miklos Racz. My research interests lie broadly in probability, high-dimensional statistics, and combinatorics. Specifically, I study random graphs with latent geometric structure with applications to network science.

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 under the supervision of Professor Jun Zhu.

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

Education

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

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

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

Publications

Preprints

• A probabilistic view of latent space graphs and phase transitions
  Suqi Liu and Miklos Z. Racz
  arXiv:2110.15886

• Phase transition in noisy high-dimensional random geometric graphs
  Suqi Liu and Miklos Z. Racz
  arXiv:2103.15249

Conference and workshop papers

• Modeling Advertiser Bidding Behaviors in Google Sponsored Search with a Mirror Attention Mechanism
  Suqi Liu, Liang Liu, Sugato Basu, Jean-Francois Crespo
  AdKDD 2019

• Who is .com? Learning to Parse WHOIS Records
  Suqi Liu, Ian Foster, Stefan Savage, Geoffrey M. Voelker, Lawrence K. Saul
  IMC 2015

Talks

• 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]

Teaching

• 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.