CSEE student awarded September 11th Memorial fellowship for AI driven transportation solution for system efficiency

By Alicia Maxwell

The NYMTC September 11^th Memorial Program for Regional Transportation Planning was created in memory of the NYMTC employees, Ignatius Adanga, See Wong Shum and Charles Lesperance, who lost their lives in the World Trade Center attacks. The program allows graduate students to experience hands-on transportation planning with an NYMTC advisor. Accepted students receive financial assistance of up to $35,000 for the one-year program. 

KC was encouraged to apply for the program by his research advisor, Dr. Ziqi Song, associate professor in the Department of Civil, Structural and Environmental Engineering. His research will focus on “Designing a freight policy tool: driving data-informed planning for the future of freight,” under the mentorship of the New York City Department of Transportation, Catherine Ponte.

“The policy tool would be a high-level document that will guide the next five to ten years of New York’s freight planning. My main target would be decarbonization of freight transportation across the state (make carbon neutral),” says KC. “I will work to design a cutting-edge tool to quantify reductions in truck vehicle miles and associated greenhouse gas emissions.”

KC interned with the National Renewable Energy Laboratory contributing to large-scale, industry-specific models for intermodal container freight logistics and fleet optimization, leveraging heuristic algorithms. His work on inclusive transport, land use and policy were selected for presentation at the Transportation Research Board annual meeting, where it also earned a certificate of recognition.

One of his most impactful projects has been on Deep Reinforcement Learning Framework to solve integrated optimization of fleet scheduling and charging management. This approach dynamically manages uncertainty in travel times caused by unexpected events. Transit agencies can get data driven decisions that minimize fleet size and operational costs while ensuring efficiency and service reliability.

“KC’s research demonstrates how artificial intelligence can transform traditional transportation operations into scalable, real-world solutions,” says Dr. Song. “By merging operational research principles with reinforcement learning, he is paving the way for more efficient transit systems.”

KC is looking forward to leveraging his unique skillset in a professional role. He aims to work in a research lab or a consulting firm as a transportational analyst.

“Receiving this prestigious fellowship is a tremendous honor and will allow me to continue my work on developing impactful, people-centered transportation solutions,” says KC. "I am confident that my work can help build a more efficient and equitable future for all.”