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Get in touch
For research collaboration, student supervision, and prospective student inquiries, please contact Dr. Baichuan Mo.
Email: bmo[at]tsinghua.edu.cn
Location
MoS Lab is based at Tsinghua University in Beijing, China.
Opportunities
Join Us
MoS Lab welcomes highly motivated students and collaborators interested in applying optimization theory and machine learning to transportation systems.
Research Directions
- Transportation system resilience: efficient optimization and machine learning algorithms to adjust operations, guide passengers, and help systems recover from incidents.
- AI for Transportation: real-time decision-making with reinforcement learning, time-series foundation models, and transportation management agents across public transit, shared mobility, and supply-chain logistics.
- Travel behavior and demand modeling: policy analysis, surveys, econometric models, and modern machine learning and optimization methods that improve traditional econometric models.
- Sustainable urban systems: commuting carbon emissions, public health risk, housing mobility, and urban cyber-physical-social system resilience.
Prospective Students
Please prepare:
- CV or resume.
- Transcript.
- Publication list, if applicable.
- A brief statement describing your research interests and how they connect with MoS Lab.
Please email Dr. Baichuan Mo at bmo[at]tsinghua.edu.cn with the materials above.