Peter Yichen Chen 陈逸尘

Postdoc
Massachusetts Institute of Technology

About Me

Hello! This is Peter. Thanks for dropping by!

My research revolves around the intersection of artificial intelligence (AI) and physics simulation. Physics simulation has arguably been the bedrock of contemporary science, engineering, and design. My overarching objective is to democratize physics simulation, ensuring accessibility to every scientist, engineer, and designer. To attain this vision, physics simulation must meet the criteria of precision, speed, generalizability, and ease-of-use. I firmly believe that achieving this objective requires a thoughtful fusion of cutting-edge AI methodologies with classical numerical methods. Indeed, this fusion has consistently formed the underlying theme of my research.

Along with my collaborators, we publish in top venues of machine learning, computer graphics, computational physics, mechanics, robotics, and more. If there is any idea that you would like to bounce off, please do not hesitate to contact me!

Currently, I am a postdoc at MIT CSAIL, working with Wojciech Matusik. I completed my CS PhD from Columbia, advised by Eitan Grinspun. Before this, I was a math undergrad from UCLA (#GoBruins).

Outside of work, I am a foodie. If I am not consuming food myself, I am probably watching mukbang videos. Food sparks joy like no other! I am always down munching together. Just let me know.

And yes, I am applying for faculty jobs this year. Happy to chat about it!

PhD dissertation

Publications

image
Neural Stress Fields for Reduced-order Elastoplasticity and Fracture
Zeshung Zong, Xuan Li, Minchen Li, Maurizio M. Chiaramonte, Wojciech Matusik, Eitan Grinspun, Kevin Carlberg, Chenfanfu Jiang, Peter Yichen Chen
SIGGRAPH ASIA, 2023
image
LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields
Yue Chang, Peter Yichen Chen+, Zhecheng Wang, Maurizio M. Chiaramonte, Kevin Carlberg, Eitan Grinspun+ (+: corresponding authors)
SIGGRAPH ASIA, 2023
image
Learning Neural Constitutive Laws From Motion Observations for Generalizable PDE Dynamics
Pingchuan Ma+, Peter Yichen Chen+, Bolei Deng, Joshua B. Tenenbaum, Tao Du, Chuang Gan, Wojciech Matusik (+: corresponding authors)
International Conference on Machine Learning (ICML), 2023
image
Learning Preconditioners for Conjugate Gradient PDE Solvers
Yichen Li, Peter Yichen Chen, Tao Du, Wojciech Matusik
International Conference on Machine Learning (ICML), 2023
image
Implicit Neural Spatial Representations for Time-dependent PDEs
Honglin Chen*, Rundi Wu*, Eitan Grinspun, Changxi Zheng, Peter Yichen Chen (*: Equal contributions)
International Conference on Machine Learning (ICML), 2023
image
CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations
Peter Yichen Chen, Jinxu Xiang, Dong Heon Cho, Yue Chang, G A Pershing, Henrique Teles Maia, Maurizio Chiaramonte, Kevin Carlberg, Eitan Grinspun
International Conference on Learning Representations (ICLR), 2023 [notable-top-25%]
image
Model Reduction for the Material Point Method via an Implicit Neural Representation of the Deformation map
Peter Yichen Chen, Maurizio Chiaramonte, Eitan Grinspun, Kevin Carlberg
Journal of Computational Physics (JCP), 2023
image
PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification
Xuan Li, Yi-Ling Qiao, Peter Yichen Chen, Krishna Murthy Jatavallabhula, Ming Lin, Chenfanfu Jiang, and Chuang Gan
International Conference on Learning Representations (ICLR), 2023 [notable-top-25%]
image
Hybrid Discrete-Continuum Modeling of Shear Localization in Granular Media
Peter Yichen Chen, Maytee Chantharayukhonthorn, Yonghao Yue, Eitan Grinspun, Ken Kamrin
Journal of the Mechanics and Physics of Solids (JMPS), 2021
image
Hybrid Grains: Adaptive Coupling of Discrete and Continuum Simulations of Granular Media
Yonghao Yue*, Breannan Smith*, Peter Yichen Chen*, Maytee Chantharayukhonthorn*, Ken Kamrin+, Eitan Grinspun+ (*: co-first authors, +: corresponding authors)
ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2018)
image
Visual Modeling of Laser-Induced Dough Browning
Peter Yichen Chen, Jonathan David Blutinger, Yorán Meijers, Changxi Zheng, Eitan Grinspun, Hod Lipson
Journal of Food Engineering, 2019
image
Characterization of CO2 Laser Browning of Dough
Jonathan David Blutinger, Yorán Meijers, Peter Yichen Chen, Changxi Zheng, Eitan Grinspun, Hod Lipson
Innovative Food Science and Emerging Technologies, 2019
image
Characterization of Dough Baked via Blue Laser
Jonathan David Blutinger, Yorán Meijers, Peter Yichen Chen, Changxi Zheng, Eitan Grinspun, Hod Lipson
Journal of Food Engineering, 2018

Preprints

image
How Can Large Language Models Help Humans in Design and Manufacturing?
Liane Makatura, Michael Foshey, Bohan Wang, Felix HähnLein, Pingchuan Ma, Bolei Deng, Megan Tjandrasuwita, Andrew Spielberg, Crystal Elaine Owens, Peter Yichen Chen, Allan Zhao, Amy Zhu, Wil J Norton, Edward Gu, Joshua Jacob, Yifei Li, Adriana Schulz, Wojciech Matusik
arXiv, 2023

Open-source software

libNCLaw: learning neural material models from motion observations

libINSR-PDE: simulating physics with implicit neural spatial representations

libCROM (Part I: training): continuous reduced-order modeling of PDEs with implicit neural representations

libCROM (Part II: deployment): continuous reduced-order modeling of PDEs with implicit neural representations

libNeuralDefMap: implicit neural representation of continuum mechanics

libPACNeRF: estimate both the unknown geometry and physical parameters of highly dynamic objects from multi-view videos

libHybridGrains: efficient simulation of granular media

libDeepBaking: machine learning modeling of laser baking