Annya Dahmani

I am a third year PhD student in the Department of Psychology at UC Berkeley, advised by Alison Gopnik. I am in the Cognition and Developmental areas with a Designated Emphasis in Cognitive Science. I am also affiliated with Berkeley AI Research. I am supported by the DoD NDSEG Fellowship and a Chancellor’s Fellowship from UC Berkeley.

I received my BS in Cognitive Science with a Specialization in Computing from UCLA in June 2022 where I graduated with Departmental Honors and Cum Laude. At UCLA, I mainly worked with Tao Gao in the Visual Intelligence Lab. I was funded by the Dean's Award for Life Science Research during my time at UCLA. I also had the opportunity to be a summer intern at Yale University working with Julian Jara-Ettinger in the Computational Social Cognition Lab.

You can email me at adahmani [at] berkeley.edu

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Research

My research is at the intersection of cognitive science and artificial intelligence, with a focus on building AI systems inspired by human cognition — particularly in learning, exploration, and reasoning. I draw on decades of research showing how humans learn rapidly and flexibly about the physical and social world, highlighting capabilities that remain beyond current state-of-the-art AI. During my PhD, I aim to use both experimental and computational approaches to study learning, decision-making, and reasoning. My recent projects include investigating automated curriculum learning in humans and machines and exploring how environmental cues—such as time horizon, safety, and controllability—influence an agent’s exploration, learning, and goal generation.

I am also passionate about leveraging insights from cognitive science to evaluate and understand the capabilities of LLMs and VLMs, and I am currently looking to expand further into this area. My interests extend to AI safety, alignment, and evaluation, where I am eager to conduct research on models' safety, alignment with human values, and effective evaluation.

Feel free to reach out to me - happy to connect!

Research keywords:

  • cognitive science
  • exploration, learning, reasoning
  • artificial intelligence
  • cognition in humans and machines