Rui-Jie Yew

I am a PhD student in computer science at Brown University and the CNTR advised by Suresh Venkatasubramanian. I'm interested in questions at the intersection of CS and policy, with an emphasis on incentives, alignment, and avoision.

Currently, I am a spring 2026 Law and Society Fellow at the Simons Institute for the Theory of Computing at UC Berkeley.

Previously, I received an S.M. in technology and policy from MIT advised by Dylan Hadfield-Menell and a joint B.A. in computer science and mathematics from Scripps College as a cross-campus major at Harvey Mudd College.

Reach me at: [my github username] at brown.edu.

profile photo outside the Calvin Lab! :)
Feb 25, 2026: Student volunteer for the 2026 SIGecom Winter Meeting on Algorithmic Game Theory, AI, and the Law. Look out for our highlights coming soon!
Feb 11, 2026: Gave a talk on Alignment Problems in AI Governance at the Simons Institute for the Theory of Computing with Greg Demirchyan. Recording available here.
Dec 05, 2025: Defended my dissertation proposal!
Sep 12, 2025: Our work on sovereign AI was covered in Rest of World.
Aug 14, 2025: Gave a talk on Red Teaming AI Policy as part of the DLA Piper guest speaker series. Thanks to the inspirational Bogdana Rakova for the invitation!
May 20, 2025: Gave a talk on Data Privacy and AI at UpperBound AI (organized by the University of Alberta) in Edmonton, Canada. Thanks to the amazing Professor Bailey Kacsmar for the invitation!
Mar 09-14, 2025: Attended Schloss Dagstuhl Seminar 25112 on privacy-enhancing technologies and AI in Wadern, Germany (where I met and reunited with my research role models). Thanks to the organizers for the invitation!
Feb 17, 2025: Gave a talk on Data Protection and AI for the Mila - Quebec AI Institute FATE and Society Reading Group. Thanks to Khaoula Chehbouni and Taylor Lynn Curtis for the opportunity to speak with such a wonderful audience!
Video Deepfake Abuse: How Company Choices Predictably Shape Misuse Patterns
Max Kamachee, Stephen Casper, Michelle L. Ding, Rui-Jie Yew, Anka Reuel, Stella Biderman, Dylan Hadfield-Menell
Under submission, 2026
Anti-Regulatory AI: How "AI Safety" is Leveraged Against Regulatory Oversight
Rui-Jie Yew, Brian Judge
ACM EAAMO, 2025
Under submission to a technology law journal
Watch Brian's talk at EAAMO here.
Red Teaming AI Policy: A Taxonomy of Avoision and the EU AI Act
Rui-Jie Yew*, Bill Marino*, Suresh Venkatasubramanian
ACM FAccT, 2025
Watch my talk at FAccT here.
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
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 CS&LAW, 2024
Poster at WeRobot, 2023
A version of this work appeared at the ICML Workshop on Generative AI and Law, 2023 spotlight (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
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

At Google, I contributed functionality to enable (ε, 0)-differential privacy with Client-Specified Partitions for Privacy on Beam for histograms. I was lucky to be mentored by Raine Serrano, Miraç Basaran, and Chris Jones.

At Sony AI, I researched privacy regulation and case law on biometric technologies, co-authoring a publication at ACM FAccT. I was lucky to be mentored by Alice Xiang.

At NIST, I contributed to the policy harmonization crosswalks connecting global policy developments with the AI Risk Management Framework. I was lucky to be mentored by Reva Schwartz and Mark Latonero.

At MIT, I was co-chair of the AI Ethics and Policy Group and organized events as part of the Research to Policy Engagement Initiative.

At Brown, I organized the first iteration of the CNTR Graduate Seminar and mentored Ashley Bao, Amanuel Tesfaye, and Ahmed Haj Ahmed as part of the Google ExploreCSR program.

My name is pronounced "Roo-Jee" in English or 叡洁 in Mandarin.

I grew up in California's East Bay and am Singaporean-American.