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Rate My Professor Tracy Ke

Harvard University

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5.00/5 · 1 review
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5.05/4/2026

Always kind, respectful, and approachable.

About Tracy

Tracy Ke is an Associate Professor of Statistics in the Department of Statistics at Harvard University. She earned her Ph.D. in Operations Research and Financial Engineering from Princeton University in 2014 and her B.S. in Mathematics and Physics from Tsinghua University in 2009. Ke began her academic career as an Assistant Professor of Statistics at the University of Chicago from 2014 to 2018. She joined Harvard University in 2018 as an Assistant Professor of Statistics and was promoted to Associate Professor in 2023. Her research centers on high-dimensional statistics, machine learning, social network analysis, text mining, bioinformatics, and statistical genetics. Ke's methodologies address challenges in sparse inference, rare and weak effects detection, and complex data structures prevalent in modern datasets.

Professor Ke has made significant contributions to statistical text analysis, network data methods, and high-dimensional inference, as recognized by prestigious awards including the 2024 COPSS Emerging Leader Award for her work in statistical text analysis, complex network data, sparse inference, rare/weak signals, and service to the community; the 2023 Alfred P. Sloan Research Fellowship in Mathematics; the 2021 IMS Peter Gavin Hall Early Career Prize; the 2020 ASA Gottfried E. Noether Young Scholar Award; the 2020 NSF CAREER Award; and the 2013 IMS Lawrence D. Brown Prize. Key publications include "Recent Advances in Text Analysis" (Annual Review of Statistics and Its Application, 2024, with Ji, Jin, Li); "Co-citation and Co-authorship Networks of Statisticians" (Journal of Business & Economic Statistics, 2022, with Ji, Jin, Li); "Using SVD for Topic Modeling" (Journal of the American Statistical Association, 2024, with Wang); "Optimal Network Membership Estimation under Severe Degree Heterogeneity" (Journal of the American Statistical Association, 2024, with Wang); "Testing High-dimensional Multinomials with Applications to Text Analysis" (Journal of the Royal Statistical Society Series B, 2024, with Cai, Turner); "Mixed Membership Estimation for Social Networks" (Journal of Econometrics, 2024, with Jin, Luo); and "Estimation of the Number of Spiked Eigenvalues in a Covariance Matrix by Bulk Eigenvalue Matching Analysis" (Journal of the American Statistical Association, 2023, with Ma, Lin). She has served as an Associate Editor for the Journal of the American Statistical Association since 2023.