Recruiting PhD for Spring/Fall 2026 @ Columbia University in the City of New York
Sharon Di (sharon.di@columbia.edu)
I am seeking to recruit 1-2 PhD students @ Columbia University starting Spring or Fall of 2026. My lab, namely, DitecT (Data and innovative technology-driven Transportation), focuses on transportation systems modeling, analysis, and simulation. I am currently focused on pioneering the development of digital twins for urban transportation management, leveraging cyber-physical systems technology, GenAI, and game theory. Details about DitecT Lab and my research can be found here: https://sharondi-columbia.wixsite.com/ditectlab/home-1.
The research directions for these PhD positions include:
- Computer Vision based on scene/knowledge graph generation and causal reasoning.
- Policy Evaluation with transfer learning using data from dash cam or infrastructure.
Expected Qualifications:
- Undergraduate or master’s degree in fields such as Computer Science, Statistics, Applied Math, Optimization, Operations Research, or related areas with a strong background in GenAI.
- Experience in computer vision, transfer learning, or game theory methods with interest in applications to transportation
- Strong mathematical and analytical skills with experience or a strong interest in autonomous driving and vision-based solutions for transportation
- Proficiency in coding and working with massive datasets
- Good communication skills, collaboration experience, and a strong motivation
Additionally, there are research opportunities for senior undergraduate and master students interested in gaining experience related to autonomous driving, computer vision, game theory, and mobility optimization. Priority will be given to students interested in applying for the PhD position.
Students interested in applying should email me at sharon.di@columbia.edu with their CV, transcript, and a brief statement on their motivation to pursue a PhD in this area at Columbia University, or directly apply via the program application portal. Please allow time for a response.