Neema Nassir

Neema Nassir's picture
Senior Postdoctoral Associate

Neema is a Senior Postdoctoral Associate at the MIT Transit Lab, and serves in research, research supervision and lecturing roles in the area of urban transportation systems at MIT. Neema's research deals with diverse and practical topics including big data analytics for public transit service planning and operations, multimodal travel demand modeling and simulation, evacuation, and traffic simulation and control. He earned his PhD in Transportation Systems from University of Arizona (2013), and his BSc. and MSc. in Civil/Transportation Engineering from Sharif University of Technology, Tehran, Iran.

Neema's current research and supervision activities are mainly focused on developing capacities for utilizing the emerging passive sources of urban mobility data (e.g. smart cards, GPS, mobile, Bluetooth, wifi, etc.) in transportation planning, operations, and management applications. This is a cluster of research and includes two important components; 1) data analysis techniques and innovative methods to understand the travel behavior and its latent complexities from the passive data, and 2) travel demand and network simulation and optimization models that can adapt to the new sources of passive data and reflect them in the decision making processes.

In his doctoral dissertation research at UA, Neema developed innovative network modeling solution methods to optimize the traffic evacuation and intersection control plan for no-notice disasters in real-size networks. He did a PhD internship at San Francisco County Transportation Authority in 2012, where he explored utility-based accessibility measures for the SFCTA’s activity-based travel demand model. After his PhD studies, he went to Australia and joined the Centre for Transport Strategy at University of Queensland (UQ). His research at UQ was mainly focused on modeling the travel behavior of public transit passengers. He has developed advanced network modeling algorithms and statistical methods to model complex travel behaviors in dense and multimodal transit networks.