Previously, I was a post-doctoral research associate at Brown University, in the Laboratory of Neural Computation and Cognition (LNCC), with Prof. Michael Frank. Here is my old web page at Brown. I studied math and science at Ecole Polytechnique (Palaiseau, France) as an undergrad, then got my PhD in Cognitive Science from UPMC (Paris, France), with Prof. Etienne Koechlin, at the laboratory for cognitive neuroscience (ENS, INSERM). You can find a full cv here.
I got my undergraduate degrees in psychology and philosophy from LMU University in Munich, Germany, then started a PhD in neuroscience at GSN in Munich, before transferring into the psychology PhD program at UC Berkeley, where I am working with Silvia Bunge and Anne Collins. I am interested in the ways we think and learn and use computational models and neurophysiological measures to answer some open questions in these fields, such as: How do we (learn to) represent the world around us? How do we infer regularities and how do we use these regularities when reasoning about the world? More fundamentally, how do we learn to infer certain regularities rather than others? That is, how do we learn to see some events rather than others as part of the same whole? I am also interested in how we learn differently at different ages, and how pubertal hormones affect brain development. I am studying this question with behavioral methods and computational modeling, combined with hormone analysis. Lastly, I am interested in the difference between habit-based and planning-based decisions, and whether practice improves decisions of each kind. I am using model-based and model-free reinforcement learning algorithms to study this question.
I obtained my undergraduate degrees in Pure Mathematics and Computational Mathematics from the University of Chicago. Currently I am a PhD candidate in Applied Mathematics at UC Berkeley. I am working with Dr. Anne Collins in using trial-by-trial modeling of the reinforcement learning system to answer questions of how humans learn and generalize previous knowledge.
I am the lab manager at the CCN Lab and a recent graduate of Brown University. At Brown I obtained a bachelors of science in cognitive neuroscience with a focus on computational neuroscience. I am interested in building computational models of decision-making and other executive control processes, as well as models of neural connectivity within the frontal lobe. Previously, I worked under Dr. David Badre and Dr. Theresa Desrochers studying the effects of anxiety on hierarchical control processes. My current work in the CCN Lab investigates how humans create and re-use structure in complex environments. In the past I've worked with fMRI, EEG, and TMS, and am looking forward to continuing to work with EEG data.
William Ryan is a Psychology Post-Baccaulaureate student at UC Berkeley, studying cognitive science and behavioral economics. He graduated Harvard in 2014 with a B.A. in Philosophy. Prior to coming to the Collins lab, he worked at TGG Group, a behavioral economics and data analysis consulting firm founded by Professors Steve Levitt and Daniel Kahneman.
Jennifer Wong is a recent graduate of UC Berkeley with a B.A. in Public Health. She is interested in further exploring human behavior and cognition, specifically decision-making and information processing. In the future, she hopes to take what she's learned to refine computational techniques in predicting human behavior and understanding how humans perceive the world. Broadly, she is interested in understanding the human experience in terms of happiness and fulfillment and how these emotions motivate certain behavior and cognitive processes.
Daniel Scott (Intern - now in the Lab for Neural Computation and Cognition (LNCC) at Brown University)
Julie Liu (Research Assistant)
Talia Welte (Undergraduate Research Assistant) Tanya Smith (Undergraduate Research Assistant)
Ching Fang (Undergraduate Research Assistant)
Gayatri Sabne (Undergraduate Research Assistant)
Benjamin Tang (Undergraduate Research Assistant)