Hi! I completed my PhD in Management Science and Engineering at Stanford University in June 2025, where I was very lucky to be advised by Prof. Ashish Goel. Prior to joining Stanford, I received my bachelor's degree at Tsinghua University, where I was very fortunate to be supervised by Prof. Pingzhong Tang and Prof. Jian Li. In the spring and summer of 2019, I went to Duke University as a visiting student, where I had the great honor to work with Prof. Debmalya Panigrahi and Prof. Kamesh Munagala.
Latest update: Aug 2025
Differential Privacy with Multiple Selections. With Ashish Goel, Aleksandra Korolova, Kamesh Munagala and Sahasrajit Sarmasarkar. FORC 2025
On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood. With Moses Charikar, Kirankumar Shiragur and Aaron Sidford. NeurIPS 2022
Online Selection Problems against Constrained Adversary. With Pinyan Lu, Zhihao Gavin Tang and Yuhao Zhang. ICML 2021
Fair for All: Best-effort Fairness Guarantees for Classification. With Anilesh K. Krishnaswamy, Kangning Wang, Yu Cheng and Kamesh Munagala. AISTATS 2021
Online Algorithms for Weighted Paging with Predictions. With Debmalya Panigrahi and Kevin Sun. ICALP 2020
Approximately Stable Committee Selection. With Kamesh Munagala and Kangning Wang. STOC 2020
Group Fairness in Commitee Selection. With Yu Cheng, Kamesh Munagala and Kangning Wang. EC 2019 / TEAC
An FPTAS for Stochastic Unbounded Min-Knapsack Problem. With Haoyu Zhao. FAW 2019
MS&E 135 Networks, Course Assistant, Winter 2025.
MS&E 111/211 Introduction to Optimization, Course Assistant, Winter 2023.
MS&E 260 Introduction to Operations Management, Course Assistant, Autumn 2022.
MS&E 111/211 Introduction to Optimization, Course Assistant, Summer 2022.
MS&E 221 Stochastic Modeling, Course Assistant, Spring 2022.
MS&E 111/211 Introduction to Optimization, Course Assistant, Winter 2022.
MS&E 260 Introduction to Operations Management, Course Assistant, Autumn 2021.
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