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Medal awarded machine learning grant

Dr. Medal is the co-PI of a grant titled “Machine-Learning-Enabled Modeling for High-Dimensional Dynamics of Materials Processes,” and funded by the StART seed funding program organized by the Science Alliance at the University of Tennessee (https://scialli.utk.edu/)

Transportation Optimization

I have done a bit of work on optimizing the design of transportation networks, mostly under the theme of usability. In a project funded by the U.S. Department of Transportation, we examined how to optimally retrofit a transportation network to make it more pedestrian-friendly (Rashidi et al., 2016). To accomplish this, we formulated an optimization model for optimally allocating limited resources to different traffic calming actions such as adding sidewalks and crosswalks. In another paper, we developed a model for designing a transportation network to make it more accessible to pedestrians (Li, Medal, and Qu, 2019).