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Ashis Gangopadhyay received his PhD in Statistics from the University of California, Davis, and his MS in Statistics from the Indian Statistical Institute. He is currently an Assistant Professor and Associate Chair at Boston University's College of Arts and Sciences, specializing in the Department of Mathematics and Statistics. His research interests include nonparametric time series prediction and smoothing, modeling financial time series, semiparametric volatility estimation, and high-frequency financial data modeling, as well as applications in epidemiology, clinical trials, and causal inference in public health research. In 2005, he received the Neu Family Award for Excellence in Teaching at Boston University, recognizing his commitment to education and mentorship.
Department of Law offers JD, LLM, and Master's in Study of Tax Law.