I'm a Ph.D. student at The Ohio State University advised by Wei-Lun (Harry) Chao .
My research investigates data and algorithmic bottlenecks that prevent autonomous driving systems from scaling to anywhere, anytime, and anyone .
These days, I've been mostly excited about data: how can we really scale self-driving toward anywhere? Should we keep putting tremendous effort into annotating 3D bounding boxes for perception? My recent work explores auto-labeling with local expert agents, such as robotaxis (ICLR 2025) and roadside units (ECCV 2026). I believe there should be more scalable ways to expand self-driving all around the world.
I also analyze effective ways to leverage LiDAR sensors for stereo depth (IROS 2026), neat autoregressive 3D detectors (CVPR 2026 Findings), and data generation for V2X perception (CVPR 2025).
I'm interning at Waymo and have previously interned at LG AI Research .
I'm an outstanding reviewer for ECCV (2022, 2024) and CVPR (2026). My ECCV 2026 work also received Best Poster Award at the CVPR 2026 DriveX Workshop .