Lab Members

John Pearson

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. In 2018, he moved back to the School of Medicine as an Assistant Professor in the Department of Biostatistics & Bioinformatics, and in 2022, he moved to the Department of Neurobiology, where he was promoted to Associate Professor in 2025. In addition, he maintains secondary appointments in the departments of Biostatics & Bioinformatics, Psychology & Neuroscience, and Electrical and Computer Engineering. (cv)

Seth Madlon-Kay

After earning a BA in psychology and economics from New York University, Seth completed his PhD in Neuroscience at the University of Pennsylvania where he used computational methods to glean new insights into the social behavior of non-human primates. His research interests include reproducible research practices and the application of probabilistic machine learning to understanding complex behavior, and he currently works on models for evidence integration in subjective legal judgements. His non-scientific activities include biking, reading Victorian novels with his wife, and attempting to appreciate jazz.

Daniela de Albuquerque

MD-PhD student

Daniela is a student at Duke's MD-PhD program. She received her B.S. in Neuroscience from Duke and wrote a senior thesis on the mechanisms of attention and working memory while working under Dr. Marty Woldorff. Before coming back to Duke, she was a post-baccalaureate research fellow at the NIMH, where she worked on developing computational screening methods for genomic and imaging biomarkers of working memory deficits in schizophrenia. As a first year ECE graduate student at Duke, she is interested in applying statistical machine-learning methods to model brain imaging data. When not in front of a computer, she loves to surf, read and hike.

Trevor Alston

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.

Miles Martinez

Electrical and Computer Engineering PhD Candidate

Miles is a fifth-year graduate student in Electrical and Computer Engineering. He entered Duke through the CNAP program. He currently develops and applies computational methods to understand the neural bases of natural learning. When not doing research, he loves getting outside and hiking or rock climbing - unless it's too cold, in which case you can find him indoors cooking or playing games.

Liz O'Gorman

Neurobiology Ph.D. Candidate

Liz is a sixth-year Ph.D. Candidate in the Department of Neurobiology. She is a recipient of the National Science Foundation Graduate Research Fellowship (NSF GRF). She is also working toward a concurrent M.S. in Electrical and Computer Engineering concentrating in Data Analytics and Machine Learning. She received her B.S. in Neuroscience and Behavioral Biology with a minor in Ethics from Oxford College and Emory College of Emory University where she worked with Dr. Donald (Tig) Rainnie and Dr. Gordon Berman. At Duke, she previously worked with Dr. Kafui Dzirasa and Dr. David Carlson. She is interested in applying computational and quantitative methods to study adaptive behaviors. Outside of lab, she builds and fixes bikes.

Ziyi Gong

Neurobiology Graduate Student

Ziyi is a fourth-year PhD candidate in Neurobiology. He received his B.S. in Computer Science with minors in Mathematics and Neuroscience from the University of Pittsburgh. He is interested in building mathematical models to summarize, explain, and predict phenomena observed in brains. Currently, he is developing models to explain how songbirds learn to sing. He previously worked with Dr. Nicolas Brunel on the roles of inhibition and inhibitory plasticity in the learning and memory of sequences. Outside of the lab he loves cooking and exercising, and occasionally plays the xiao (Chinese flute).

David St-Amand

Neurobiology Graduate Student

David is a third-year graduate student in Neurobiology. 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

Electrical and Computer Engineering PhD Student

Shiyang is a graduate student in Electrical & Computer Engineering at Duke. She received her Bsc in Applied Mathematics from University of Liverpool and Xi'an Jiaotong-Liverpool University. 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

Electrical & Computer Engineering PhD Student

Caitlin is a first-year 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 populations. Outside of the lab, she enjoys reading and playing pickleball with friends.