E-Mail:
mail at paulgoelz dot de
Paul Gölz
I’m an assistant professor in the School of Operations Research and Information Engineering at Cornell and a member of the Computer Science field. I think about new ways of doing democracy (e.g., citizens’ assemblies), about how to fairly allocate resources (e.g., capacity to host refugees), and developing AI for heterogeneous users (e.g., generative social choice). I developed and maintain Panelot.org, a not-for-profit selection tool for citizens’ assemblies.
Before joining Cornell, I did my undergrad at Saarland University in Germany, got my PhD in computer science at Carnegie Mellon University, and did postdocs at Harvard, the Simons Laufer Mathematical Sciences Institute (formerly: MSRI), and UC Berkeley.
I have the pleasure of supervising Hannane Yaghoubizade (ORIE 2nd year, joint with David Williamson).
I enjoy getting to know new people and chatting about research. Whether you're a researcher, a student interested in research, a practitioner, or just curious, please don’t hesitate to reach out!
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Distortion of AI Alignment: Does Preference Optimization Optimize for Preferences?.
Paul Gölz,
Nika Haghtalab,
and Kunhe Yang.
In submission.
[Preprint]
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Putting fair division on the map.
In submission.
[Preprint]
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Generative social choice.
[Preprint]
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Monotone randomized apportionment.
[Preprint]
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In this apportionment lottery, the House always wins.
Paul Gölz,
Dominik Peters,
and Ariel Procaccia.
Operations Research.
Supersedes C12.
Forthcoming.
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Dynamic placement in refugee resettlement.
Operations Research (2024) Communications of the ACM research highlight.
Supersedes C8.
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Now we’re talking: Better deliberation groups through submodular optimization.
Jake Barrett,
Kobi Gal,
Paul Gölz,
Rose Hong,
and Ariel Procaccia.
[Preprint]
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Mini-public selection: Ask what randomness can do for you.
Bailey Flanigan,
Paul Gölz,
and Ariel Procaccia.
Harvard Kennedy School Ash Center. Policy Briefs (2023).
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Social choice for social good: Proposals for democratic innovation from computer science.
Paul Gölz.
Ph.D. thesis, 2022.
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Approval-based apportionment.
Mathematical programming (2022).
Supersedes C6.
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In this apportionment lottery, the House always wins.
Paul Gölz,
Dominik Peters,
and Ariel Procaccia.
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Fair allocations for smoothed utilities.
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Envy-free and Pareto-optimal allocations for agents with asymmetric random valuations.
Yushi Bai
and Paul Gölz.
[Full paper]
[Code]
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Fair algorithms for selecting citizens’ assemblies.
Nature (2021).
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Incentive-compatible kidney exchange in a slightly semi-random model.
Avrim Blum
and Paul Gölz.
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Dynamic placement in refugee resettlement.
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The fluid mechanics of liquid democracy.
ACM Transactions on Economics and Computation (2021).
Supersedes C2.
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Neutralizing self-selection bias in sampling for sortition.
[Full paper]
[Code]
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Approval-based apportionment.
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Paradoxes in fair machine learning.
Paul Gölz,
Anson Kahng,
and Ariel Procaccia.
NeurIPS 2019 Spotlight presentation (2.5% of submissions).
[Full paper]
[Code]
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No stratification without representation.
Gerdus Benadè,
Paul Gölz,
and Ariel Procaccia.
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Migration as submodular optimization.
Paul Gölz
and Ariel Procaccia.
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The fluid mechanics of liquid democracy.
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Synthesis in distributed environments.
Bernd Finkbeiner
and Paul Gölz.
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Synthesis for Petri games with one system player.
Paul Gölz.
Undergraduate thesis, 2017.
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