Peyman is a Postdoctoral Associate at MIT Transit Lab and Urban Mobility Lab. He earned his PhD in Transportation Systems from Northeastern University, and his BSc in Civil Engineering from Sharif University of Technology.
During his doctoral dissertation research, he developed real-time predictive models for short-term transit demand prediction. He also developed a transit simulation software which was used to predict crowding on trains and station platforms. In another application, he used Deep Learning and natural language processing techniques for text mining and analysis of incident reports. He is currently working on projects with Transport for London, as well as the Mass Transit Railway in Hong Kong.
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