Richard Guo

Richard Guo is an Assistant Professor of Statistics at the University of Michigan, Ann Arbor. He holds a PhD in Statistics from the University of Washington (2021) and an MS in Computer Science from Duke University (2016). His research focuses on replicable data analysis, causal inference foundations, and uncertainty quantification. Guo previously served as a Research Associate at the University of Cambridge and a Richard M. Karp Fellow at the Simons Institute. He has developed software tools like the MultiSplit R package for hypothesis testing with multiple data splits. His awards include the Richard M. Karp Research Fellowship (2022) and the Z. W. Birnbaum Award (2019–2020).

Education:

• PhD in Statistics, University of Washington, 2021
• MS in Computer Science, Duke University, 2016
• BEng in Computer Science, University of Electronic Science and Technology of China, 2013

Research Interests:

• Replicable data analysis: randomized procedures and derandomization
• Causal inference: graphical models, nonparametric methods
• Uncertainty quantification: model selection, finite-sample guarantees

Awards:

• Richard M. Karp Research Fellowship, Simons Institute (2022)
• Z. W. Birnbaum Award, University of Washington (2019–2020)

Teaching:

• Instructor for graduate courses on linear models and probability theory at University of Washington
• Guest lectures on causal DAGs and statistical modeling