Academic appointments
- 2020–present
Assistant Professor of Statistics
Department of Statistics, University of Chicago. Affiliated Scholar, Data Science Initiative.
Education
- 2015–2020
Ph.D. in Statistics · Stanford University
Advised by Susan Holmes and Jure Leskovec. Dissertation: Uncertainty Quantification in Complex Networks with Applications to Brain Connectomics. Mind, Brain, Computation and Technology graduate trainee, 2018–2020.
- École Polytechnique
Engineering diploma and M.Sc. in Applied Mathematics
Diplôme d’Ingénieur Polytechnicien; M.Sc. in Applied Mathematics, Data Science track. Palaiseau, France.
- 2010–2012
Lycée Sainte-Geneviève
MPSI/MP* preparatory program in mathematics and physics. Versailles, France.
Selected research funding
- 2026–2029
NIH R01 · Spatially-Informed AI to Dissect Complex Cell-State Transitions in Tissue Niches
Co-PI, with lead PI Samantha Riesenfeld and Thomas Gajewski.
- 2025–2028
NSF IOS/EB · Evolution and Mechanisms of Thermotolerance in Cyanobacteria
Co-PI, with lead PI Freddy Bunbury.
- 2025
NITMB Internal Grant
Multimodal Data Analysis for Uncovering Host-Microbiome Responses to Environmental Stress.
- 2023–2028
NSF CAREER · Towards Responsible Graph Neural Networks
Principal investigator. Award No. 2238616.
- 2023
University of Chicago FACCT Grant
Statistical Properties of Graph Neural Network Embeddings, with Olga Klopp.
- 2021
Facebook Research Award
Learning to Trust Graph Neural Networks, in the Statistics for Improving Insights, Models, and Decisions program. Award announcement.
Selected honors
- 2026
ICML Gold Reviewer
- 2023
NSF CAREER Award
- 2022
Simons–Google Fellow
Graph Limits and Processes on Networks: From Epidemics to Misinformation workshop.
- 2020
First place · COVID-19 research challenges
C3.ai COVID-19 Grand Challenge, Lumiata COVID-19 Hackathon, and COVIDathon.
- 2019
University Centennial Teaching Award
Stanford University.
- 2016
Departmental Teaching Assistant Award
Department of Statistics, Stanford University.
Professional service
- Area chair: ICLR 2023; NeurIPS 2025–2026.
- Conference reviewer: ICML 2019–2026; NeurIPS 2020–2024; CVPR 2022.
- Journal reviewer: TMLR, JASA, The Annals of Statistics, and Statistical Science.
- NSF panelist: Division of Mathematical Sciences, Statistics Panel B, winter 2021.
- Statistical consulting: co-leads the University of Chicago Statistics Consulting Program with Mei Wang.
Earlier research and industry experience
- 2019
HAIL Research Fellow · Hudson River Trading
Deep-learning methods for time series and market-structure analysis. New York.
- 2018
Ph.D. Research Intern · Facebook Core Data Science
Graph classification for understanding user-group dynamics. Menlo Park, California.
- 2017
Quantitative Research Intern · G-Research
Statistical and machine-learning analysis of financial data. London.
- 2015
Visiting Graduate Scholar · Johns Hopkins University
Research in René Vidal’s Vision Lab on scalable sparse subspace clustering for computer vision. Received a Research Internship Award from École Polytechnique’s Department of Applied Mathematics.
See my publications, teaching, and talks, or visit the SIGNAL Lab for current projects and group members.