I produce music under both aliases AlexHe and Elykz, experimenting among the genres of House, Hip-hop and New-age. My original music has gathered over 2 million streams across platforms.
[2026.02] I'm joining Google DeepMind as a student researcher.
[2025.08] I'm starting my Ph.D. studies at Cornell University.
[2025.06] Our work ERNet is accepted to ICCV 2025. See you in Honolulu!
[2025.02] Our work CANOR is accepted to CVPR 2025. See you in Nashville!
[2024.06] I'm visiting Stanford Vision and Learning Lab as a research intern.
[2024.01] Our work 4K4D is accepted to CVPR 2024.
[2023.07] Our work EasyVolcap is accepted to SIGGRAPH Asia 2023 TC.
Publication
My research interests lie at the intersection of Computer Vision and Reasoning, particularly in the representation, understanding and long-term memory of dynamic 3D scenes, with the goal of enabling machines to perceive the dynamic and diverse world as humans do.
A feed-forward representation that encodes deformable 4D objects into a sparse set of spatially-grounded blobs to disentangle pose and instance information, enabling intuitive pose manipulation while preserving rich instance-specific information.
A feed-forward pipeline that registers any object template onto a sequence of non-rigidly deforming point clouds, with 4.6x faster inference speed and 2x better accuracy than previous SOTA.
A novel point-based 4D representation reconstructed with multi-view videos, which can be rendered at 4k 200+ FPS with state-of-the-art quality on a single RTX 4090.
A Python & PyTorch library for accelerating volumetric video research, particularly in the area of neural dynamic scene representation, reconstruction, and rendering.