About
Asohan Amarasingham is a Professor at the City University of New York (CUNY), affiliated with both City College and the Graduate Center. He holds a B.Sc. in Mathematics & Cognitive Science from the University of Virginia (1997), an M.Sc. in Cognitive & Linguistic Sciences from Brown University (1999), and a Ph.D. in Applied Mathematics from Brown (2004). His postdoctoral training was with György Buzsáki at Rutgers University. His research focuses on statistics, neural coding, and computational neuroscience, emphasizing large-scale neurophysiological data analysis and neuronal circuit dynamics.
His academic career includes teaching mathematics courses such as Elements of Calculus and Statistics, Probability Theory, and Applied Statistics. Notable advisees include Ben Tupper, who joined the PhD program at the Graduate Center in 2025. His work spans statistical methodologies for neural spike analysis, including studies on spike train reliability, temporal coding, and ensemble activity dynamics.
Key contributions include rejecting the Poisson hypothesis in neural spike variability, analyzing hippocampal and prefrontal cortical assemblies, and developing statistical tools for neurophysiological data. His interdisciplinary approach bridges applied mathematics, neuroscience, and computational modeling.
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