Rui-Jie Yew

I am a PhD student in computer science at Brown University, where I am fortunate to be advised by Suresh Venkatasubramanian at the Center for Technological Responsibility, Reimagination, and Redesign (CNTR). I conduct interdisciplinary research in computer science, law, and policy. My work has received honors at AAAI/ACM AIES, ACM DIS, and the ICML Workshop on Generative AI and Law and has been cited in the popular press.

In fall 2025, I am an IvyPlus Exchange Scholar at MIT EECS in machine and multiagent learning.

Outside of my research work as a PhD student, I have experience in privacy engineering at Google, AI ethics at Sony AI, AI risk management and standards at the National Institute of Standards and Technology, and research mentorship as part of the Brown exploreCSR program (where my student won a best project award!).

I started the Brown CNTR Graduate Seminar on Technology and Society and have organized for the MIT AI Policy group and the MIT IDSS Research to Policy Engagement Initiative.

I am happy to chat about research and graduate school. You can contact me at rjy [at] alum.mit.edu. You can find my CV here.

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Research
Anti-Regulatory AI
Rui-Jie Yew, Brian Judge
Forthcoming at ACM EAAMO, 2025
Red Teaming AI Policy: A Taxonomy of Avoision and the EU AI Act
Rui-Jie Yew*, Bill Marino*, Suresh Venkatasubramanian
ACM FAccT, 2025
Copyrighting Generative AI Co-Creations
Jeff Huang, Rui-Jie Yew, Suresh Venkatasubramanian
ACM DIS, 2025 **Best Paper Award**
You Still See Me: How Data Protection Supports the Architecture of AI Surveillance
Rui-Jie Yew, Lucy Qin, Suresh Venkatasubramanian
ACM/AAAI AIES, 2024 **Best Student Paper Runner-Up Award**
A version of this work was presented at the Privacy Law Scholars Conference, 2024
NeurIPS Workshop on Regulatable ML, 2023
Break It 'Til You Make It: An Exploration of the Ramifications of Copyright Liability Under a Pretraining Paradigm of AI Development
Rui-Jie Yew
ACM Symposium on Computer Science and Law, 2024
Poster at WeRobot, 2023
A version of this work appeared at the ICML Workshop on Generative AI and Law, 2023 **Spotlight Presentation** (with Dylan Hadfield-Menell)
Where did you learn that?: Tracing the Impact of Training Data with Diffusion Model Ensembles
Zheng Dai, Rui-Jie Yew, David K. Gifford
NeurIPS Workshop on Regulatable ML, 2023
Measuring the Success of Diffusion Models at Imitating Human Artists
Stephen Casper*, Carl Guo*, Shreya Mogulothu, Chinmay Deshpande, Rui-Jie Yew, Zheng Dai, Dylan Hadfield-Menell
ICML Workshop on Generative AI and Law, 2023 **Spotlight Presentation**
A Penalty Default Approach to Preemptive Harm Disclosure and Mitigation for AI Systems
Rui-Jie Yew, Dylan Hadfield-Menell
AAAI/ACM AIES, 2022
Regulating Facial Processing Technologies: Tensions Between Legal and Technical Considerations in the Application of Illinois BIPA
Rui-Jie Yew, Alice Xiang
ACM FAccT, 2022
Ethical Dilemmas in Strategic Games
Pavel Naumov, Rui-Jie Yew
AAAI, 2021

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