Yanfei Zhou (周砚菲)

About me

I am a third-year Ph.D. student in the Department of Data Sciences and Operations (DSO) at the University of Southern California (USC), Marshall School of Business. At USC, I am working with Professor Matteo Sesia on Conformal Inference and Deep Learning.

Before joining USC Marshall, I completed my Master's degree in Statistics at the University of Chicago and my Bachelor's degree in Statistics with Finance at the London School of Economics (LSE). In addition, I also worked as a Data Scientist at CNA Insurance from Aug 2020 to Mar 2021.

A short version of my CV; Linkedin homepage

Publications

Conformal Forecaster for Heterogeneous time Trajectories [paper]

Yanfei Zhou, Lars Lindemann, and Matteo Sesia. ArXiv Pre-Print

Conformal inference is (almost) free for neural networks trained with early stopping [paper, poser]

Ziyi Liang*, Yanfei Zhou*, and Matteo Sesia. ICML 2023

*Equal Contribution

Training Uncertainty-Aware Classifiers with Conformalized Deep Learning [paper, poster]

Bat-Sheva Einbinder, Yaniv Romano, Matteo Sesia, and Yanfei Zhou*. NeurIPS 2022

*alphabetical order

Research

My current research projects are mainly about Uncertainty Quantification (UQ) for machine learning and deep learning model predictions. Specifically, we calibrate the model using a conformal inference framework to estimate predictive uncertainty. In the future, I am interested in exploring topics including online learning, causal machine learning, natural language processing, and reinforcement learning.

Contact

If you are interested in academic collaborations or want to know more about our Ph.D. program, please contact me via yanfei.zhou@marshall.usc.edu. I'm also actively looking for a summer internship as a Research Scientist or Applied Scientist.

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