studies AI and Law at Cornell University's Department of Information Science. His recent academic affiliations include fellowships at the Princeton Polaris Lab, the Stanford RegLab, and the Institute for Law & AI.
Prior to starting his PhD, Dan spent several years contributing to research and policy around emerging technologies—mostly at places with “Center” in their name—including the Center for Democracy & Technology, the Stanford Cyber Policy Center, and the Center on Privacy & Technology at Georgetown Law, where he now serves on the Advisory Board.
His work has been supported by the MacArthur Foundation through the Artificial Intelligence, Policy, and Practice initiative, a Google Public Policy Fellowship, and a Thomas J. Watson Fellowship. He holds a Master of Law and Technology from Georgetown University Law Center and a B.A. from Middlebury College.
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Selected work
| Hidden in Plain Text: LLM-Assisted Detection of Discriminatory Local Laws | International Conference on Artificial Intelligence and Law (ICAIL) | 2026 |
| RCTs for Human-AI Evaluation: Methodological Challenges and Practical Solutions | RAND Working Paper + AIES | 2026 |
| One Bad NOFO? AI Governance in Federal Grantmaking | ACM FAccT | 2025 |
| Bureaucratic Backchannel: How r/PatentExaminer Navigates AI Governance | Sociotechnical AI Governance workshop @ CHI | 2025 |
| Human-AI Collaboration workshop @ ACM EC | 2025 |
Shelved
| Mapping Funding Landscapes of Civil Society and Public Interest Technologies: Voids, Trends, and Stakes | Talk @ PLSC | 2025 |
| Poster @ AIPP | 2024 | |
| Internet Law Works in Progress | 2024 |