I am a fifth-year Ph.D. Candidate in Engineering-Economic Systems at the CS and AI Laboratory and the College of Computing, MIT. I study how platforms learn what users want and decide who gets what online, and why. My supervisors Alessandro Bonatti, Dylan Hadfield-Menell, Eric Maskin and David Parkes guide me through this adventure.

📧 • CV • Linkedin • Github • G Scholar

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Selected Writing. Risk Aversion of Learning Algorithms (R&R GEB) • Contextual Privacy (ACM EC ‘22) • Towards Psychologically Plausible Dynamic Preference Models (ACM RecSys ‘22) • Optimal Equilibria via Zero-Sum Games (Neurips ‘23) • Certification Design for a Competitive Market (Marketplace Innovation Workshop ‘23) • Recommending to Strategic Users (FORC ‘23) • Formal Contracting for Multi-Agent Reinforcement Learning (ACM SIGAI AAMAS ‘23) • Auctions for Federated Learning (ICLR ‘21 DPFL) • Understanding Single- and Multi-Homing on Transportation Platforms (TR: C) • Our Class Can’t Happen (letter) • Opaque Mechanisms • Comment for Data Access Delegated Act of the European Union Digital Services Act: Experimental Data • Steering No-Regret Learners • The Economics of Social Network Interoperability (memo)

Selected Work in Progress. Optimal Preferencing Design I: Statics • Optimal Preferencing Design II: Dynamics • Relational Contracts Mitigate Social Dilemmas • Recommendation based on Regret Signals

Experiences. Federal Trade Commission • European Commission • Bundestag • MITx • Professional School Gross-Gerau.

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Recent Leadership. Science Policy Initiative • MIT AI Ethics&Policy • GSC Sustainability.

Co-Organized Events. Technical Questions on the EU AI Act • Algorithmic Audits in Economic Contexts • Wastewater Surveillance • Data Externalities

Selected Teachers. Erik Brynjolffson • Jonathan Zittrain • Ash Carter • Costis Daskalakis • Glenn Ellison • Parag Pathak • Mohammad Akbarpour and Shengwu Li • Leslie Kaelbling • Victor Chernozhoukov

Studies and Theses. B.Sc. Mathematics • M.Sc. Mathematics • M.Sc. Economics • B.Sc. Computer Science