Dan is an Assistant Professor in Yale’s Department of Neuroscience, and a Wu Tsai investigator at the WTI Center for Neurocomputation and Machine Intelligence. He received his B.S. in Biochemistry with a minor Physics from Northeastern University, his M.S. in Biophysics from Cornell University, and his PhD in Neuroscience from New York University under the mentorship of György Buzsáki and John Rinzel. He then did postdoctoral research at the interface of neuroscience and artificial intelligence at McGill University and Mila, the Quebec AI Institute, with Adrien Peyrache and Blake Richards. Dan’s scientific interests lie at the interface of biology, dynamics, and computation, where he enjoys collaborating with experimental colleagues. When not in the lab, he enjoys hiking, board games, weird music, and a good book.

Andrea is a postdoctoral researcher working jointly with Dan Levenstein and Tristan Geiller. She enjoys figuring out how circuits of neurons encode information, with a primary focus on spatial learning and decision making. She received her bachelor’s degree in neuroscience at New York University, where she worked with Luke Sjulson in Gyuri Buzsáki’s lab. During her undergraduate research, she conditioned mice to prefer a cocaine-paired location to investigate how hippocampal input to the ventral striatum mediates drug-associated spatial memories. For her PhD, she joined Jozsef Csicsvari’s lab at the Institute of Science and Technology Austria, shifting her focus to the brains of sober rodents. There, she designed a novel associative learning task and found a subset of neurons in the hippocampus and prefrontal cortex that flicker between distinct spatial representations. As a postdoc, she works at the interface of data analysis and computational modeling to examine information representation in the hippocampus and beyond. Her current project focuses on evaluating how a virtual environment is represented by mouse CA3 and a predictive RNN. She also enjoys listening to drum and bass, climbing mountains, and reading techno[dys/u]topian science fiction.

Aidan is a Wu Tsai Institute Postdoctoral Fellow collaborating closely with the Levenstein lab, among others. He is interested in how transient, localized “sleep-like” states emerge during wakefulness and influence neural computation. As a postdoc, he uses multi-scale neural recordings, theoretical frameworks from statistical mechanics and information theory, and machine-learning models to explore how local sleep dynamics regulate cortical activity across space and time. He earned a B.S. in Molecular Biosciences and Biotechnology from Arizona State University and a Ph.D. in Computational and Systems Biology from Washington University in St. Louis. During his Ph.D., he worked with Keith Hengen to study how genetic identity, anatomical location, and arousal state shape neural activity, leveraging complex microelectrode recordings in freely behaving animals and novel machine-learning models. Key to his ongoing research is the discovery of a non-oscillatory, spatiotemporally localized embedding of arousal state in the brain, reflected in brief, local non-oscillatory sleep events—or “flickers”—that transiently disrupt ongoing behavior and network coordination. Outside the lab, he enjoys tabletop role-playing games, walks in East Rock Park, and doting on his cats, Smokey and Bird.

I am a master’s student in Computational Biology at Yale University. My current research interests focus on the spontaneous activity and self-organization of neural networks. Before coming to Yale, I earned my Bachelor’s degree in Biotechnology from the Technion – Israel Institute of Technology. My previous research experience includes bioinformatics analysis, building biophysical neuron models, and conducting large-scale neural network simulations. At Yale, I joined the lab to explore how spontaneous neural activity during sleep contributes to task performance through homeostatic plasticity.

Viggy Vanchinathan is a recent graduate from Johns Hopkins University, where he majored in Biomedical Engineering and Applied Mathematics. There, he conducted research in labs across both departments, most notably leading a design team in a project to characterize functional impairment in Parkinson's patients using machine learning and movement data. He’s also worked for biotech startups and is quite interested in entrepreneurship. He joined the lab as a Postgraduate Associate and computational lab assistant in October 2025. Outside of the lab, he enjoys lifting, cooking, and writing food reviews on Google Maps.

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