Yulun Tian

Yulun Tian is an Assistant Professor in the Robotics Department at the University of Michigan, where they direct the Scalable Spatial Intelligence Lab. Their research focuses on developing scalable and trustworthy autonomy for long-term operation without human intervention, integrating tools from nonlinear/distributed optimization, machine learning, and graph theory to create robust spatial perception, navigation, and multi-agent systems with theoretical guarantees.

• PhD, MIT AeroAstro (2023)
• SM, MIT (2019)
• BA, UC Berkeley (2017)

Research spans robotic perception (e.g., learned representations, robust estimation), distributed autonomy for multi-agent systems, and optimization algorithms for navigation. Key projects include Kimera-Multi (2022 IEEE T-RO award) and MISO (RSS 2025), emphasizing neural implicit reconstruction and Laplacian solvers for rotation averaging.

Selected publications highlight trends in distributed SLAM, multi-agent coordination, and learning-based spatial intelligence. Awards include the 2024 IEEE RAS TC Best Dissertation Award and 2022 IEEE T-RO Best Paper Award. They served as Associate Editor for IROS 2025 and IJRR since 2024.

Prospective PhD students are encouraged to apply with interests in optimization for autonomy, spatial perception, and distributed systems. The lab emphasizes theoretical guarantees and real-world applications in autonomous systems.