Speaker: Dr. Maria Rita D’Orsogna
Via Zoom: https://ucla.zoom.us/j/93503114400
Abstract: There is considerable interest in developing quantitative models to better inform engineering solutions to psychiatric and social issues. For example, the design and impact of deep brain stimulation, electroshock, or exposure therapies could greatly benefit from a description of their effects within mechanistic models of the relevant cognitive processes. Such models offer a foundation on which to interpret data, make quantitative predictions, and validate interventions. In this talk, I will summarize examples in which paradigms from dynamical systems, network theory, and game theory have been applied to problems in cognitive and social sciences. In a detailed example, I will present a dynamical model that unifies psychiatric concepts such as neuroadaptation, expectation, and learning to describe features of drug addiction, and to help guide mitigation strategies. These research directions incorporate modeling with data and offer an attractive educational platform for increasing representation of underrepresented groups in science and engineering. I will present some potential initiatives based on these areas of research.
Biography: Maria R. D’Orsogna received her PhD in Physics from UCLA in 2003. She is currently the Associate Director of the Institute for Pure and Applied Math at UCLA and a Professor of Mathematics at California State University at Northridge (CSUN), a minority serving institution. Her scientific interests cover topics in computational psychiatry, sociology, and biology that she studies using quantitative approaches such as dynamical systems, game theory, data analysis, stochastic processes, and numerical simulations. Her work is supported by the NSF, NASA and the Army Research Office. As an advocate for EDI, she has helped create bridges between UCLA and CSUN, has led educational and activist campaigns for the environment, and guided CSUN students into research and PhD programs.
Date(s) - Feb 02, 2021
11:00 am - 12:30 pm