Yongxu Jin

Machine Learning Engineer
Apple
San Francisco Bay Area, CA
jin.yongxu at outlook.com
Github
Linkedin

Biography

Greetings! I am a Machine Learning Enginner at Apple, working on Vision Pro and neural rendering related projects. I received my Ph.D. degree in Department of Computer Science, Stanford University, advised by Prof. Ron Fedkiw. I graduated from Shanghai Jiao Tong University with a B.S.E. degree in Software Engineering. During my undergraduate years, I was a research intern in Digital ART Lab (DALAB), where I worked with Prof. Bo Zhu on computational fluid dynamics, and Prof. Xubo Yang on virtual reality.

My research interest lies in the intersection of CG and AI. Specifically, I am interested in reconstructing and animating realistic digital human (body, clothing, face, etc.) by combining physics-based and learning-based methods.

Education

Stanford University, Sep. 2019 - Jul. 2024
Ph.D. in Computer Science
Thesis: Combining Neural Networks and Physics-based Simulation for Cloth and Flesh Dynamics

Shanghai Jiao Tong University, Sep. 2015 - Jul. 2019
B.S.E. with Honors in Software Engineering
Thesis: Computational Models for Implicit Surface Tension on Lagrangian Structures

Work Experience

Apple, Aug. 2024 - Present, Jun. 2023 - Sep. 2023
Neural rendering.

Epic Games, Oct. 2020 - Jun. 2024
Digital human clothing and soft tissue animation.

Meta Reality Lab Research, Jun. 2022 - Sep. 2022, Jun. 2020 - Sep. 2020
(1) Yarn-level cloth simulation using XPBD. (2) Body composition optimization from motion data.

Cloudpense, Dec. 2017 - Feb. 2018
Invoice image processing and OCR.

Publications

A Neural-Network-Based Approach for Loose-Fitting Clothing
Yongxu Jin, Dalton Omens, Zhenglin Geng, Joseph Teran, Abishek Kumar, Kenji Tashiro, Ronald Fedkiw
arXiv:2404.16896

Paper Video

Software-based Automatic Differentiation is Flawed
Daniel Johnson, Trevor Maxfield, Yongxu Jin, Ronald Fedkiw
arXiv:2305.03863

Paper

Analytically Integratable Zero-restlength Springs for Capturing Dynamic Modes unrepresented by Quasistatic Neural Networks
Yongxu Jin, Yushan Han, Zhenglin Geng, Joseph Teran, Ronald Fedkiw
ACM SIGGRAPH 2022 Conference proceedings

Paper Video

Recovering Geometric Information with Learned Texture Perturbations
Jane Wu, Yongxu Jin, Zhenglin Geng, Hui Zhou, Ronald Fedkiw
ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA 2021)

Paper

Codimensional Surface Tension Flow using Moving-Least-Squares Particles
Hui Wang, Yongxu Jin, Anqi Luo, Xubo Yang, Bo Zhu
ACM Transaction on Graphics (SIGGRAPH 2020)

Paper Video Two Minute Papers

ToonNet: A cartoon image dataset and a DNN-based semantic classification system
Yanqing Zhou, Yongxu Jin, Anqi Luo, Szeyu Chan, Xiangyun Xiao, Xubo Yang
ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry (VRCAI 2018)

Paper

Miscellaneous

My first name 'Yongxu' can be pronounced as 'Yong-Shoe'.

I am grateful to Prof. Robert Bridson's book, Fluid Simulation for Computer Graphics, which helps me start my research career.

Math for Computer Graphics

GAMES: Graphics And Mixed Environment Seminar (计算机图形学与混合现实研讨会).

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