Hi, I'm Jeffrey! I'm a first year PhD student at the University of Cambridge supervised by Professor Ayush Tewari.
Previously, I was a research engineer at the GraphDeco group in INRIA with Professor George Drettakis.
I was also an active contributor to gsplat.
Before this, I worked on autonomous vehicles and building the perception system for autonomous trains
at Parallel Systems in Los Angeles. I received my undergraduate and Master's degrees in Electrical Engineering and
Computer Science at MIT with Professor Antonio Torralba.
I am deeply interested in 3D computer vision, computer graphics, and differentiable rendering. I
want to capture and build generative models for the real world.
gsplat is an open-source library designed for training and developing Gaussian Splatting methods. It
features a front-end with Python bindings compatible with the PyTorch library and a back-end with
highly optimized CUDA kernels. gsplat offers numerous features that enhance the optimization of
Gaussian Splatting models, which include optimization improvements for speed, memory, and
convergence times. Experimental results demonstrate that gsplat achieves up to 10% less training
time and 4x less memory than the original implementation. Utilized in several research projects,
gsplat is actively maintained on GitHub. Source code is available at this https URL under Apache License 2.0.
We welcome contributions from the open-source community.
