First-year CIS PhD Student, University of Pennsylvania
Advised by Prof. Kostas Daniilidis at the GRASP Lab
I build systems that combine 3D computer vision and generative models to understand motion and enable intelligent, visually guided robots. Broadly, I'm excited about the intersection of 3D vision, graphics, and embodied AI. I'm currently seeking research internship opportunities — if you think there's a good match, feel free to reach out.
Previously, I was a research intern at Stanford University, working with Prof. Leonidas Guibas, Dr. Adam W. Harley, and Prof. Shangzhe Wu. I also spent a year at UC Berkeley with the Nerfstudio team at BAIR, under Prof. Angjoo Kanazawa. I received my undergraduate degree from ShanghaiTech University.
Outside of research, I play the piano, shoot photography, and fly drones. I'm also an avid traveler — so far I've explored over 20 countries and regions across five continents.
A policy that maintains a belief over an articulated object's joint type and parameters, acting to maximize the information each interaction reveals about its hidden kinematics.
A comprehensive framework for learning and generating 3D quadruped motion directly from large-scale video data.
A pipeline for dense animal pose annotation by optimizing general-purpose point trackers — fine-tuning a lightweight appearance embedding from a few annotated frames to label an entire video with minimal supervision.
Recovering human avatars from self-occluded internet videos where people show only parts or sides of their body.
An open-source library for CUDA-accelerated differentiable rasterization of 3D Gaussians with Python bindings. I worked on the Python bindings, CUDA testing, and alpha-channel rendering.
A modular framework for neural radiance field development. I worked mainly on the integration of Gaussian splatting.
