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Luise Ge
email /
CV /
photos /
thoughts
I am a Computer Science PhD student at Washington University in St Louis, advised by Yevgeniy Vorobeychik and Brendan Juba.
Currently, I am interested in automated group decisions (e.g. combining social choice theory and alignment together), dealing with diverse user preferences, integrating learning and reasoning, and the foundations of AI in general.
I started out as a cognitive science student at the University of Edinburgh, with the passion to figure out how mind works. While this curiosity has never diminished, it just happened that the beauty of maths struck me greatly.
I ended up getting a master degree specialised in geometry and topology at Imperial College London under the guidance of the amazing Paolo Cascini. My master thesis was on algebraic geometry inspired by a fantastic idea called "the periodic table of shapes".
I have turned back to CS due to both the philosophical considerations and social impact of many computational problems.
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News
- [May 2025] Our paper Learning Policy Committees for Effective Personalization in MDPs with Diverse Tasks is accepted into ICML 2025!
- [April 2025] Our paper Polynomial-Time Relational Probabilistic Inference in Open Universes is accepted into IJCAI 2025!
- [Oct 2024] I am going to attend the 10th Conference of Algorithmic Decision Theory at DIMACS, Rutgers University.
- [Sep 2024] Our paper Axioms for AI Alignment from Human Feedback is accepted into Neurips Spotlights!
- [May 2024] I will be presenting at the AAMAS 2024 Workshop on Social Choice and Learning Algorithms in Auckland, New Zealand
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Research
Social Choice and Value Alignment:
Axioms for AI Alignment from Human Feedback
(α-β) Luise Ge, Daniel Halpern, Evi Micha, Ariel D. Procaccia, Itai Shapira, Yevgeniy Vorobeychik, Junlin Wu
✦Spotlight✦ in the 38th Annual Conference on Neural Information Processing Systems (NeurIPS), 2024.
Learning Linear Utility Functions From Pairwise Comparison Queries
Luise Ge, Brendan Juba and Yevegniy Vorobeychik
Fair allocation: implementing and evaluating an algorithm for competitive allocation of chores
Outstanding undergraduate thesis supervised by Kousha Etessami
Integration of Learning and Reasoning:
Polynomial-Time Relational Probabilistic Inference in Open Universes
(α-β) Luise Ge, Brendan Juba, Kris Nilsson
the 34th International Joint Conference on Artificial Intelligence(IJCAI), 2025.
Meta-Learning:
Learning Policy Committees for Effective Personalization in MDPs with Diverse Tasks
Luise Ge, Michael Lanier, Anindya Sarkar, Bengisu Guresti, Yevgeniy Vorobeychik, Chongjie Zhang
the 42nd International Conference on Machine Learning (ICML), 2025.
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