Yu Gui
Welcome to my homepage!

I am a Postdoctoral Researcher in the Department of Statistics and Data Science at the Wharton School, University of Pennsylvania, working with Professor Dylan Small and Professor Zhimei Ren.
I obtained my PhD in Statistics at the University of Chicago, where I was fortunate to be advised by Professor Rina Foygel Barber and Professor Cong Ma.
Prior to my PhD, I graduated from School of the Gifted Young at University of Science and Technology of China and was a student research intern advised by Professor Jun S Liu at Harvard.
My research broadly focuses on theory and methodology in scenarios where the distribution is weakly specified or fully supervised data are unavailable. I am particularly interested in statistical inference with adaptively collected data, distribution-free inference under distribution shifts, and learning with multi-modal data.
news
May 18, 2025 | New preprint: multi-modal contrastive learning adapts to intrinsic dimensions presents a theoretical analysis of CLIP and its ability to adapt to the intrinsic dimension of multimodal data enabled by temperature optimization. |
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Apr 08, 2025 | I’ve passed my PhD defense! Starting in July 2025, I’ll be working as a postdoctoral researcher in the Department of Statistics and Data Science at the Wharton School, working with Professors Dylan Small and Zhimei Ren. |
Apr 02, 2025 | Our paper Conformal Prediction: A Data Perspective has been accepted to ACM Computing Surveys. |
Sep 26, 2024 | Our paper Conformal Alignment has been accepted to NeurIPS 2024! This paper guarantees the safe and reliable deployment of foundation model outputs. |
Jul 10, 2024 | A new preprint iso-DRL on how to utilize side information (e.g. shape constraints) to balance the misspecification of sample reweighting and the over-pessimism of distributionally robust learning! As an application, iso-DRL suggests a robust approach to calibrate estimated density ratios in reweighting approaches. |
Jun 30, 2024 | I’m thrilled to be awarded the William Rainey Harper Dissertation Fellowship! |
Dec 31, 2023 | Presented conformalized matrix completion at NeurIPS 2023 and ICSDS 2023. |
Mar 30, 2023 | Received IMS Hannan graduate student award for our work on theory of contrastive learning. |