Jianfeng Chi's Homepage
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PhD Candidate Email: jc6ub(AT)virginia(DOT)edu [Google Scholar] [Twitter] [LinkedIn] [Github] |
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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.
[arXiv]
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
[arXiv]
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