Christian Nielsen-Garcia (He/Him)
Ph.D. in Information Studies
I am a Ph.D. student in Information Studies at UCLA, where my research centers on AI, swarm intelligence, collective intelligence, and multi-agent systems. I research how disagreement, conflict, and dialogue shape group decision-making, problem-solving, and coordination. My doctoral committee is chaired by Ramesh Srinivasan (UCLA Information Studies), alongside Geoffrey Bowker (UC Irvine), Jonathan Furner (UCLA Information Studies), PJ Lamberson (UCLA Communication), and Moritz Meyer-ter-Vehn (UCLA Economics). My work is conducted with ongoing gratitude for guidance and research funding from the SSRC, Mellon Foundation, UC Berkeley Center for Responsible Decentralized Intelligence (RDI), the Center for Digital Assets (CDA), and the Mercatus Center.
Degree Program
Expected Graduation Year
Interests
Faculty Advisor
Education
- BA, Cornell University, 2020
- MSc The University of Copenhagen, 2023
Awards, Honors, and Fellowships
- Mercatus Fellowship, Mercatus Center at George Mason University, 2026–2027
- Alexis de Tocqueville Fellowship, Mercatus Center at George Mason University, 2026
- Center for Digital Assets Research Award, UC Berkeley, 2026
- AI & Decentralization Innovation Award, UC Berkeley RDI, 2025
- GSE Predoctoral Research Grant, SSRC–Mellon Mays, 2024–2025
- Educational and Professional Fund Research Grant, University of Copenhagen, 2022–2023
- Certificate of Achievement, Center for AI and Digital Policy, 2022
- Mellon Mays Undergraduate Research Fellowship, Cornell University, 2018–2020
Select Presentations
Co-author, “Position: Benchmarking is Broken — Don’t Let AI Be Its Own Judge,” accepted to NeurIPS 2025 (Conference on Neural Information Processing Systems), to be presented November 2025.
Select Publications
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Nielsen Garcia, C., et al. (2025). “Position: Benchmarking is Broken—Don’t Let AI Be Its Own Judge.” Accepted to NeurIPS 2025 (39th Conference on Neural Information Processing Systems).
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Nielsen Garcia, C. (2026). “The Geometry of Decision-Making in DAOs: An Information-Theoretic Mapping of Consensus and Disagreement in Decentralized Token Voting.” Preprint, available at SSRN.