Jianfeng Chi's Homepage

PhD Candidate
Department of Computer Science
University of Virginia

Email: jc6ub(AT)virginia(DOT)edu

[Google Scholar] [Twitter] [LinkedIn] [Github]

 

About Me


I am a PhD student in the Department of Computer Science at University of Virginia. Currently, I work on fairness and privacy of machine learning and ML for security and privacy. My advisor is Prof. Yuan Tian. Previously, I obtained my B.Eng. degree from Beijing University of Posts and Telecommunications in 2017.

Selected Publications / Preprints


Understanding and Mitigating Accuracy Disparity in Regression (ICML 2021)
Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon and Han Zhao.
[PDF] [Codes]

Intent Classification and Slot Filling for Privacy Policies (ACL 2021)
Wasi Uddin Ahmad*, Jianfeng Chi*, Tu Le, Thomas Norton, Yuan Tian, Kai-Wei Chang
[PDF] [Codes] [Video]

Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation (NeurIPS 2020)
Jianfeng Chi*, Han Zhao*, Yuan Tian and Geoffrey J. Gordon.
[PDF] [Poster] [Slides]

PolicyQA: A Reading Comprehension Dataset for Privacy Policies (Findings of EMNLP 2020)
Wasi Uddin Ahmad*, Jianfeng Chi*, Yuan Tian and Kai-Wei Chang.
[PDF] [Codes]

Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries (USENIX Security 2020)
Fnu Suya, Jianfeng Chi, David Evans, and Yuan Tian.
[PDF] [Codes]

* indicates equal contributions, listed by alphabetical order.


For a full list of my publications/manuscripts, please go to my Google Scholar webpage.

Industry Experiences


Facebook, Inc.
Ads Core ML
Software Engineer Intern, Machine Learning (PhD)
Mentor: Eric Ma

Amazon Web Services, Inc.
Machine Learning Research and Security Analytics, Amazon GuardDuty
Applied Scientist Intern
Mentor: Dr. Luca Melis and Dr. Baris Coskun

Professional Services


PC Member/Reviewer:
IEEE S&P 2021, AAAI 2021-2022, NeurIPS 2021, ICML 2021, ICLR 2022
USENIX Security'18 Posters, ICLR DPML 2021, AAAI PPAI 2022