Guy Davidson
Guy Davidson

PhD Candidate

NYU Center for Data Science

About Me

I’m a cognitive scientist and PhD candidate at the NYU Center for Data Science, advised by Brenden Lake and Todd Gureckis. I’m excited about understanding the human mind and leveraging ideas from human cognition to develop more human-like artificial intelligence. My dissertation (writing in progress) offers theoretical, empirical, and computational advances in the study of goals: how do we represent, reason about, and come up with them? Recently I’ve become interested in similar questions around large language models, which has led me to starting working on language model interpretability (which I currently do as a visiting researcher at Meta FAIR).

In my non-academic life, I live with my wife Sarah and our dog Lila, and spend time making homemade hot sauces, playing board games, and lifting weights.

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Interests
  • Goal representation and generation
  • Human-like goals for agents
  • Compuational cognitive science
  • Goal/intent inference in LLMs
Education

  • PhD in Data Science

    New York University

  • MPhil in Data Science

    New York University

  • BSc in Computational Sciences

    Minerva University

Projects
Goals as Reward-Producing Programs
Infant Relation Categorization
Playful Goal Modeling
Simple Object Representations
Publications
Guy Davidson, Graham Todd, Julian Togelius, Todd M. Gureckis, Brenden M. Lake (2024). Goals as Reward-Producing Programs. In press, Nature Machine Intelligence.
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Guy Davidson, Todd M. Gureckis (2024). Toward Complex and Structured Goals in Reinforcement Learning. Finding the Frame @ RLC 2024.
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Guy Davidson, A. Emin Orhan, Brenden M. Lake (2024). Spatial relation categorization in infants and deep neural networks. Cognition.
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Sugandha Sharma, Guy Davidson, Khimya Khetarpal, Anssi Kanervisto, Udit Arora, Katja Hofmann, Ida Momennejad (2024). Toward Human-AI Alignment in Large-Scale Multi-Player Games. Wordplay @ ACL 2024, Association for Computational Linguistics.
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Guy Davidson, Graham Todd, Todd M. Gureckis, Julian Togelius, Brenden M. Lake (2023). Generating Human-Like Goals by Synthesizing Reward-Producing Programs. Intrinsically Motivated Open-Ended Learning @ NeurIPS 2023.
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Guy Davidson, Todd M. Gureckis, Brenden M. Lake (2022). Creativity, Compositionality, and Common Sense in Human Goal Generation. Proceedings of the 44th Annual Meeting of the Cognitive Science Society, CogSci 2022.
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Daniel Bennett, Guy Davidson, Yael Niv (2022). A model of mood as integrated advantage. Psychological Review.
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Guy Davidson, Brenden M. Lake (2021). Examining Infant Relation Categorization Through Deep Neural Networks. Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, CogSci 2021.
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Guy Davidson, Brenden M. Lake (2020). Investigating Simple Object Representations in Model-Free Deep Reinforcement Learning. Proceedings of the 42nd Annual Meeting of the Cognitive Science Society, CogSci 2020.
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Guy Davidson, Brenden M. Lake (2020). Systematically Comparing Neural Network Architectures in Relation Learning. Object-Oriented Learning (OOL): Perception, Representation, and Reasoning @ ICML 2020.
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Guy Davidson, Michael C. Mozer (2020). Sequential mastery of multiple visual tasks: Networks naturally learn to learn and forget to forget . The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
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Guy Davidson, Angela Radulescu, Yael Niv (2019). Contrasting the effects of prospective attention and retrospective decay in representation learning. The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making.
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Daniel Bennett, Guy Davidson, Yael Niv (2019). Momentum and mood in policy-gradient reinforcement learning. The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making.
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