PhD in Computer Vision and Game Theory: Columbia University is recruiting PhD students to join an innovative research group led by Dr. Xuan (Sharon) in Fall 2026. The opportunity is for students who wish to work at the border of Game Theory, Applied Mathematics, Computer Science, Data Science, and Electrical Engineering.
Students will work on projects that combine theory and practical influence that will positively impact urban mobility, safety, and equity using advanced data-driven techniques.
Why Pursue a PhD at Columbia University?
Financial Support: This program provides financial aid in respect to tuition fees, and other research costs, such as conference and research travel expenses.
Best Research Culture: Students enjoy the best research facilities, great volumes of data, and a strong academic community.
Research Topic: The project focuses on data- and technology-driven transportation research. The lab’s mission is rooted in empowering mobility for all and applying technology for social good.
Strong Mentorship and Career Development: PhD students work closely with Dr. Di and collaborators across Columbia. Graduates are well-positioned for careers in academia, industry, research labs, policy organizations, and technology companies, shaping the future of mobility.
Program Description – PhD in Computer Vision and Game Theory
The DitecT Lab is actively working on several forward-looking research directions. Incoming PhD students will contribute to one or more of the following ongoing projects:
- Generative models for data generation (including methodological development for diffusional models, LLM models)
- Policy Evaluation with Transfer Learning based on various sensors, such as dash cam and infrastructure-based cameras
- VR/AR development for Traffic Simulation and Digital Twin Development
- PDE models to model and simulate rare events
Qualifications For PhD in Computer Vision and Game Theory
Ideal candidates will have:
- Undergraduate or master’s degree in fields such as Computer Science, Data Science, Operations Research, or related areas, with a strong background in computer vision or statistics.
- Experience in computer vision, VR/AR experimentation, 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 strong motivation
Application Process For PhD in Computer Vision and Game Theory
Students interested in applying for this PhD position should contact Dr. Sharon Di. Attach the following documents to the email:
- A current CV
- Academic transcripts
- A brief statement describing your motivation to pursue a PhD in this research area
Alternatively, applicants can directly apply via the program application portal via: Click here
About Dr Sharon
Dr. Sharon Di is an Associate Professor in the Department of Civil Engineering and Engineering Mechanics at Columbia University in the City of New York. She directs the DitecT (Data and innovative technology-driven Transportation) Lab, focusing on innovative transportation systems research.
Her overarching mission is to empower mobility for all, with a strong emphasis on using technology for social good. Currently, her research encompasses autonomous vehicle control on shared roads, multi-modal mobility optimization, and transportation-health intersections.
Why This PhD Opportunity Is Unique
By joining the DitecT Lab at Columbia University, students will:
- Work on cutting-edge AI and data science methods applied to transportation
- Contribute to the development of digital twins for real cities
- Gain experience with autonomous driving and smart infrastructure systems
- Collaborate across disciplines in a global research hub
- Build a strong foundation for leadership roles in research and innovation
Deadline and Contact Information
Application Deadline: The application deadline is December 15. Early contact is encouraged, cause priority will be given to students who apply early.