Matthew Cong

Principal Research Scientist, NVIDIA
Ph.D. Computer Science, Stanford University
B.S. Engineering Physics and Computer Science, Cornell University
Santa Clara, CA
LinkedIn

Biography

Matthew received his Ph.D. in Department of Computer Science at Stanford University in 2016 where he was advised by Professor Ron Fedkiw and supported by a National Defense Science and Engineering Graduate Fellowship. Currently, Matthew works as a Principal Research Scientist at NVIDIA on the Omniverse team. From 2012 to 2020, he worked as a Research and Development Engineer at Industrial Light & Magic focusing on facial animation and simulation. He has received screen credits for this work on "Kong: Skull Island", "Avengers: Endgame", and "The Irishman".

Prior to attending Stanford, Matthew received his B.S. in Engineering Physics and Computer Science from Cornell University in 2011. As an undergraduate, he worked on computational ab initio physics and electrochemistry as well as path planning for personal robotics. Matthew was also an intern at Morgan Stanley in 2010.

Publications

An Interface Tracking Method with Triangle Edge Cuts
Mengdi Wang, Matthew Cong, and Bo Zhu
Journal of Computational Physics 520, 113504 (2025)

arXiv

fVDB: A Deep-Learning Framework for Sparse, Large-Scale, and High-Performance Spatial Intelligence
Francis Williams, Jiahui Huang, Jonathan Swartz, Gergely Klár, Vijay Thakkar, Matthew Cong, Xuanchi Ren, Ruilong Li, Clement Fuji-Tsang, Sanja Fidler, Eftychios Sifakis, and Ken Museth
SIGGRAPH 2024, ACM TOG 43, 4, Article 133 (July 2024)

arXiv

Near-realtime Facial Animation by Deep 3D Simulation Super-Resolution
Hyojoon Park, Sangeetha Grama Srinivasan, Matthew Cong, Doyub Kim, Byungsoo Kim, Jonathan Swartz, Ken Museth, and Eftychios Sifakis
ACM Transactions on Graphics (TOG), 2024

arXiv

Local Geometric Indexing of High Resolution Data for Facial Reconstruction from Sparse Markers
Matthew Cong, Lana Lan, and Ronald Fedkiw
arXiv:1903.00119 (March 2019) and IEEE Transactions on Visualization and Computer Graphics (TVCG), 2023

arXiv PDF Video

High-Quality Face Capture Using Anatomical Muscles
Michael Bao, Matthew Cong, Stéphane Grabli, and Ronald Fedkiw
arXiv:1812.02836 (Dec 2018) and The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019

arXiv PDF Video

Art-Directed Muscle Simulation for High-End Facial Animation
Matthew Cong, Kiran Bhat, and Ronald Fedkiw
ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA), edited by L. Kavan and C. Wojtan, pp. 119-127 (2016).

PDF Video

Automatic Generation of Anatomical Face Simulation Models
Matthew Cong, Michael Bao, Jane E, Kiran Bhat, and Ronald Fedkiw
ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA), edited by F. Bertails-Descoubes and S. Coros, pp. 175-183 (2015).

PDF Video

Codimensional Surface Tension Flow on Simplicial Complexes
Bo Zhu, Ed Quigley, Matthew Cong, Justin Solomon, and Ronald Fedkiw
SIGGRAPH 2014, ACM TOG 33, 4, Article 111 (July 2014)

PDF Video

A New Grid Structure for Domain Extension
Bo Zhu, Wenlong Lu, Matthew Cong, Byungmoon Kim, and Ronald Fedkiw
SIGGRAPH 2013, ACM TOG 32, 63.1-63.8 (2013)

PDF Video

Simulating Free Surface Flow with Very Large Time Steps
Michael Lentine, Matthew Cong, Saket Patkar, and Ronald Fedkiw
ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA), edited by P. Kry and J. Lee, pp. 107-116 (2012)

PDF Video

Talks

Teaching