Lab Members

Meet our group
John Pearson

John Pearson

Principal Investigator

John earned his bachelor's degree in physics and math from the University of Kentucky and his PhD in physics from Princeton. He became a neuroscientist at Duke, where he did his postdoctoral training with Michael Platt, working on the neurobiology of reward and decision-making. From 2015 to 2018, he was an Assistant Research Professor in the Duke Institute for Brain Sciences, and from 2018-2025, he was an Assistant Professor in Biostatistics & Bioinformatics and Neurobiology. Since 2026, he has been an Associate Professor in the Center for Neural Science at NYU, with an affiliation at the Center for Computational Neuroscience at the Flatiron Institute. (cv)

Ganchao Wei

Ganchao Wei

Postdoc

Ganchao plays around with stats / ML / AI, mainly motivated by and applied to neuroscience. He is currently into deep generative models (diffusion-/flow-based) and causal representation learning.

Trevor Alston

Trevor Alston

Neurobiology PhD Student

Trevor is a sixth-year Neurobiology graduate student at Duke University. He holds two Biomedical Engineering Degrees; he received his BS degree from Rutgers University and his MS degree from Northwestern University. His research interest is in Neuroengineering and brain-related technologies. Outside of the lab he likes hanging out with friends, playing games, and watching TV.

David St-Amand

David St-Amand

Neurobiology Graduate Student

David is a third-year graduate student in Neurobiology at Duke. He graduated from McGill University, where he received his BS in Psychology and his MS in Neuroscience. His research investigates how efficient coding models can help us understand how information is computed in the retina. Outside the lab, he likes to work out and play games.

Shiyang Pan

Shiyang Pan

Center for Data Science PhD Student

Shiyang is a graduate student in the Center for Data Science at NYU. She received her Bsc in Applied Mathematics from University of Liverpool and Xi'an Jiaotong-Liverpool University and her master's in electrical and computer engineering from Duke. Her research focuses on developing computational models and real-time methods to understand the activity of large-scale neural populations. When not doing research she enjoys music, reading, and creative writing.

Caitlin Lewis

Caitlin Lewis

Electrical & Computer Engineering PhD Student

Caitlin is a graduate student in Electrical & Computer Engineering at Duke. She received her B.S. in Computer Science and Statistics from the University of North Carolina at Chapel Hill. Her research focuses on developing computational models and open-source software tools for real-time analysis and visualization of large-scale neural data. Outside of the lab, she enjoys reading and playing pickleball with friends.


Former members

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