Research
My research is at the intersection of cognitive science and artificial intelligence, with a focus on building AI systems inspired by human cognition â 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 cuesâsuch as time horizon, safety, and controllabilityâinfluence an agentâs 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
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