Erin Mitchell is a graduate student researcher at the MIT Center for Transportation & Logistics (MIT CTL), where she is pursuing a Master of Science in Transportation. Her research focuses on applying operations research, machine learning, and advanced analytics to logistics and transportation systems, with an emphasis on translating complex data into practical decision support.
At MIT CTL, Erin’s work centers on port and freight systems, examining how operational data can be used to better understand system performance and inform planning and decision-making. Her research explores integrating forecasting and analytical models with decision processes to improve efficiency, resilience, and sustainability in supply chains.
Prior to MIT CTL, Erin spent several years in professional data analytics roles related to air traffic management, designing machine learning models and decision support tools for complex operational systems. Erin holds a Bachelor’s degree in Industrial and Operations Engineering from the University of Michigan, where she conducted research in healthcare engineering and medical logistics.
