INFORMS Open Forum

MIT Summer Course Announcement: Discrete Choice Analysis & Transportation Networks and Smart Mobility

  • 1.  MIT Summer Course Announcement: Discrete Choice Analysis & Transportation Networks and Smart Mobility

    Posted 6 days ago

    Dear Colleagues,

    We will be offering 2 one-week MIT courses live in Zoom this summer:

    Discrete Choice Analysis: Predicting Individual Behavior and Market Demand

    June 6 – 10, 2022

    This course covers alternative models including Logit, Probit, Nested Logit, Multivariate Extreme Value, discrete and continuous Logit Mixtures and Hybrid Choice Models; and alternative estimation methods including simulated maximum likelihood, Hierarchical Bayes, instrumental variable methods and random effects in panel data.  Recent additions include "Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis" by Moshe Ben-Akiva, Daniel McFadden and Kenneth Train, estimation of flexible model specifications using machine learning methods and online applications for optimization and personalization.  Each day consists of lectures followed by a computer lab to apply the lectured methods with open-source software and data sets. Initial lectures and lab sessions review required fundamental concepts.

    The course is intended for both academics and professionals. Partial scholarships (50%) are available for junior faculty, postdocs, and doctoral students.

    Transportation Networks and Smart Mobility: Methods and Solutions

    August 1 – 5, 2022

    This course presents newly developed data analytics, models and simulation tools for use in the planning, design, and operations of transportation systems including Intelligent Transportation Systems, Smart Mobility, public transportation and emerging modes, freight and e-commerce, and congestion pricing.  Methods covered include: traffic simulation, static and dynamic network models, equilibrium and dynamic algorithms, passenger and freight demand and user behavior, passenger and freight sensing, machine learning applications, data fusion to estimate origin to destination flows, calibration and validation of simulators, and online platform for prediction, optimization and personalization of smart mobility.

    This course is intended for individuals interested in theory, research and practice, including: professionals in the mobility industry, transportation consulting, planning and related government agencies, PhD students in transportation systems, civil engineering, economics, planning and urban mobility, traffic engineering, systems engineering, operations management and control systems.

    One full-tuition scholarship will be awarded to an outstanding doctoral student with an application deadline of June 15, 2022.  Partial scholarships (50%) are available for junior faculty, postdocs, and doctoral students.

    We appreciate your help in making people aware of these unique opportunities to study this summer at MIT.

    Thank you, Moshe



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    Moshe Ben-Akiva
    Massachusetts Institute of Technology
    Edmund K. Turner Professor of Civil & Environmental Engineering
    Director, Intelligent Transportation Systems Lab
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