Chulin Xie

Hi! I am a second-year Ph.D. student in Computer Science at University of Illinois at Urbana-Champaign, advised by Prof. Bo Li. Before that, I received my Bachelor degree in the CS Department, Zhejiang University in July 2020. I was an intern at Visual Computing Group of Microsoft Research Asia.

My current research interests include machine learning, adversarial robustness, privacy, fairness, federated learning, representation learning and distributed optimization.


[05/2022] I start my summer internship at AI Algorithm team @ NVIDIA Research, hosted by Prof. Anima Anandkumar and Dr. Chaowei Xiao.


Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM
Chulin Xie, Pin-Yu Chen, Ce Zhang, Bo Li
In submission

Certified Robustness for Free in Differentially Private Federated Learning
Chulin Xie, Yunhui Long, Pin-Yu Chen, Krishnaram Kenthapadi, Bo Li
NeurIPS 2021 New Frontiers in Federated Learning Workshop

RVFR: Robust Vertical Federated Learning via Feature Subspace Recovery
Jing Liu, Chulin Xie, Krishnaram Kenthapadi, Oluwasanmi O Koyejo, Bo Li
NeurIPS 2021 New Frontiers in Federated Learning Workshop


Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses
Micah Goldblum, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein
TPAMI 2022

CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
Chulin Xie, Minghao Chen, Pin-Yu Chen, Bo Li
ICML 2021
[Paper] [Code] [Poster]

Style-based Point Generator with Adversarial Rendering for Point Cloud Completion
Chulin Xie*, Chuxin Wang*, Bo Zhang, Hao Yang, Dong Chen, Fang Wen
CVPR 2021
[Paper] [Code] [Poster] [Project]

DBA: Distributed Backdoor Attacks against Federated Learning
Chulin Xie, Keli Huang, Pin-Yu Chen, Bo Li
ICLR 2020
[Paper] [Code] [Slides for Federated Learning One World Seminar (FLOW)]

Attack-Resistant Federated Learning with Residual-based Reweighting
Shuhao Fu, Chulin Xie, Bo Li, Qifeng Chen
AAAI 2021 Towards Robust, Secure and Efficient Machine Learning Workshop


Last update: May, 2022