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 NLP 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.

I will join Facebook Inc. working as a Software Engineer Intern, Machine Learning (PhD) in summer 2021.

Selected Publications / Preprints

Understanding and Mitigating Accuracy Disparity in Regression (to appear in ICML 2021)
Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon and Han Zhao.

Intent Classification and Slot Filling for Privacy Policies (to appear in ACL 2021)
Wasi Uddin Ahmad*, Jianfeng Chi*, Tu Le, Thomas Norton, Yuan Tian, Kai-Wei Chang

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

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:
USENIX Security'18 Posters, AAAI 2021, IEEE S&P 2021, ICML 2021, ICLR DPML Workshop 2021