CVPR 2025: Published 'Sonata: Self-Supervised Learning of Reliable Point Representations', achieving 3x higher linear probing accuracy on ScanNet and 2x performance with only 1% training data.
Arxiv 2024: Led the release of 'EFM3D: A Benchmark for Measuring Progress Towards 3D Egocentric Foundation Models', establishing the first benchmark and baseline model EVL.
CVPR 2024: Co-authored 'EgoLifter: Open-world 3D Segmentation for Egocentric Perception', using Gaussian Splats for reconstruction and instance segmentation of Project Aria data.
CVPR 2023: Contributed to Omni3D, a large-scale 3D object detection benchmark with 234k images, 3M+ instances, and 98 categories; proposed the generalizable Cube R-CNN model.
CVPR 2023: Co-developed OrienterNet, the first deep network to localize images using 2D semantic maps from OpenStreetMap.
CVPR 2023: Co-proposed PARQ for multi-view 3D object detection from short posed video sequences.
Invited speaker at major conferences including ICCV 2025, CVPR 2025, and ECCV 2024 on topics like 3D perception, point clouds, and egocentric AI.