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Ph.D in Decision Neuroscience (economics),
and minor in Computer Science, Caltech
I am a behavioral scientist trying to build important cognitive foundations in basic market and economics activity. There are two secret ingredients that help me getting there: novel datasets (eye-tracking, response time) and machine learning techniques.
keywords: machine learning, behavioral economics, experimentation, saliency and attention
Highlight Papers:
Highlight Papers:
Li, Xiaomin, and Colin F. Camerer. "Predictable Effects of Visual Salience in Experimental Decisions and Games." The Quarterly Journal of Economics 137.3 (2022): 1849-1900.
Hidden Markov modeling of the cognitive process in strategic thinking, April 2023, with Thomas Henning and Colin Camerer Front. Behav. Econ., 19 October 2023
New neuroeconomic ideas about habit: Neural autopilot, with Colin Camerer, Current Opinion in Behavioral Sciences 41 (2021): 185-190
"What can machine learning teach us about habit formation? Evidence from exercise and hygiene." Proceedings of the National Academy of Sciences 120.17 (2023): e2216115120, with Buyalskaya, Anastasia, et al.
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