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Simon Jerome Han

To avoid confusion: my first name is Simon but everyone calls me by my middle name, Jerome. Please call me Jerome!

Prospective PhD applicants: I am committed to helping minimise the hidden curriculum that drives the admissions process at places like Stanford. If you have any questions about your application or if you would like to know more about what applying is like in general, I'm happy to chat! Email me (address is at the top of my CV) or shoot me a message on LinkedIn. I've also written up a brief Q&A about the process, available below. Good luck!

Hello from Stanford, CA!

I am a PhD student in the psychology department at Stanford. Before this I was a machine learning engineer at Canva, where I worked on applied NLP and CV for recommender systems, and before that I completed my undergraduate degree at the University of Melbourne, where I studied Psychology and Computer Science.

I am broadly interested in the intersection between machine learning and cognitive science. At the level of individuals, I am interested in the computational processes that underpin higher order cognitive abilities such as reasoning and problem solving. At the level of cultures, I am interested in using large natural datasets paired with recent advances in machine learning to better understand the context that shapes our daily lives.

I want to live in a world where boring things are easily automated and people are empowered to spend more of their time discovering and working on whatever they most care about. My long term goal is thus to build flexible AI systems that learn and think like we do, but faster and more transparently too.

In my spare time I like to run, eat and admire interesting architecture.


Han, S. J., Ransom, K. J., Perfors, A. & Kemp, C. (2023). Inductive reasoning in humans and large language models. Cognitive Systems Research.

Han, S. J., Kelly, P., Winters, J. & Kemp, C. (2022). Simplification is not dominant in the evolution of Chinese characters. Open Mind.

Han, S. J., Ransom, K. J., Perfors, A. & Kemp, C. (2022). Human-like property induction is a challenge for large language models. Proceedings of the 44th Annual Meeting of the Cognitive Science Society.

Butavicius, M., Taib, R., & Han, S. J. (2022).Why people keep falling for phishing scams: The effects of time pressure and deception cues on the detection of phishing emails. Computers and Security.

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