Professor Ugander's research develops algorithmic and statistical frameworks for analyzing social networks, social systems, and other large-scale data-rich contexts. He is particularly interested in the challenges of causal inference and experimentation in these complex domains. His work commonly falls at the intersections of graph theory, machine learning, statistics, optimization, and algorithm design.

Honors & Awards

  • NSF CAREER Award, National Science Foundation (2022)
  • Outstanding Problem-Solution Paper Award, AAAI Conference on Web and Social Media (ICWSM) (2021)
  • Best Paper Award, AAAI Conference on Web and Social Media (ICWSM) (2020)
  • Faculty Teaching Award, ICME, Stanford (2020)
  • ARO Young Investigator Award, Army Research Office (2019)
  • Hellman Faculty Fellow, Stanford University (2019)
  • Eugene L. Grant Undergraduate Teaching Award, Management Science & Engineering, Stanford (2016)
  • Faculty Award, Facebook (2016)
  • Best Student Paper Award, ACM Conference on Web Search and Data Mining (WSDM) (2013)
  • Best Paper Award, ACM International Conference on Web Science (WebSci) (2012)

Program Affiliations

  • Symbolic Systems Program

Professional Education

  • PhD, Cornell University, Applied Mathematics (2014)

2023-24 Courses

Stanford Advisees