Yihong Gu
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I'm a Postdoctoral Research Fellow at the Department of Biomedical Informatics, Harvard Medical School, advised by Prof. Tianxi Cai. I obtained my Ph.D. from the Department of Operations Research and Financial Engineering at Princeton University, where I was fortunate to be advised by Prof. Jianqing Fan. Before Princeton, I got my bachelor's degree in the Department of Computer Science and Technology at Tsinghua University.
My research spans nonparametric statistics, deep learning, causal inference, distribution estimation, variable selection, factor models, and their applications in health studies. Here are some topics I am working on:
Statistical and causal learning using multi-source data
Fundamental limits in statistical estimation
Deep learning for statistical estimation
Statistical analysis of modern machine learning models/algorithms
Recent Papers
Fundamental limits in statistical estimation using black-box models
Y. Gu. Optimal use of a black-box model in semiparametric estimation. arXiv. 2026.
Y. Gu, Q. Yin, T. Cai, J. Fan. Optimally taming biases in black-box models for efficient semiparametric estimation. arXiv. 2026.
Pursuing invariance and causality from heterogeneous environments
Y. Gu, K. Liao, T. Cai. Unveiling the invariant factors across heterogeneous environments via ATLAS. arXiv. 2026
Y. Gu, C. Fang, Y. Xu, Z. Guo, J. Fan. Fundamental Computational Limits in Pursuing Invariant Causal Prediction and Invariance-Guided Regularization. arXiv. 2025.
Y. Gu, C. Fang, P. Bühlmann, J. Fan. Causality pursuit from heterogeneous environments via neural adversarial invariance learning. Annals of Statistics. 53(5): 2230-2257, 2025.
J. Fan, C. Fang, Y. Gu, T. Zhang. Environment invariant linear least squares. Annals of Statistics. 52(5): 2268-2292, 2024.
Statistically efficient estimation using neural networks
J. Fan, Y. Gu. Factor Augmented Sparse Throughput Neural Networks for High Dimensional Regression. Journal of the American Statistical Association. 119(548), 2680–2694, 2024.
J. Fan, Y. Gu, W.-X. Zhou. How do noise tails impact on deep ReLU networks? Annals of Statistics. 52 (4): 1845-1871, 2024.
Awards
Charlotte Elizabeth Procter Fellowship, Princeton University, 2024 [News]
IMS Hannan Graduate Student Travel Award, Institute of Mathematical Statistics, 2024
ASA Best Student Paper Award, ASA Business and Economic Statistics Session, 2024
School of Engineering and Applied Science Award for Excellence, Princeton University, 2023 [News]
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