Minchen Li 李旻辰

Assistant Professor, CMU CSD, Carnegie Mellon Graphics Lab

Ph.D., University of Pennsylvania, Computer and Information Science, 2020
M.Sc., University of British Columbia, Computer Science, 2018
B.Eng. (Hons), Zhejiang University, Computer Science and Technology, 2015

Research focus: Integrating Physical Simulation with AI for Computer Graphics,
Visual Computing, Robotics, and Computational Mechanics.

Email | Google Scholar | Research Gate | Github | Twitter | Zhihu

Minchen is an assistant professor in the Computer Science Department at Carnegie Mellon University, having joined in September 2023 after leaving his role as an assistant adjunct professor at UCLA Department of Mathematics, AIVC Lab. He was a postdoctoral researcher in the SIG Center for Computer Graphics at the University of Pennsylvania after completing his Ph.D. in the same group, advised by Chenfanfu Jiang. Minchen is a winner of the 2021 ACM SIGGRAPH Outstanding Doctoral Dissertation Award and the 2021 Symposium on Computer Animation (SCA) Doctoral Dissertation Award. His Ph.D. dissertation features the Incremental Potential Contact (IPC) method, which "presents a breakthrough in the notoriously challenging and long-standing problem of robust frictional contact simulation in nonlinear solid dynamics with guarantees of non-intersection" and has led to a series of follow-up works in both academia and industry. Minchen received his M.Sc. in Computer Science from the University of British Columbia in 2018, advised by Alla Sheffer.


The efficacy of solid and fluid simulation methods in the evolving landscape of visual computing, manufacturing, and robotics industries is fundamentally determined by robustness, efficiency, accuracy, and versatility. However, achieving a harmonious balance among these crucial characteristics remains an open challenge. The Simulation Intelligence Group (SIG) led by Minchen is committed to advancing the frontiers of physical simulation by striving for unprecedented levels of performance in all these areas, leveraging a comprehensive approach that combines numerical analysis, high-performance computing, and machine learning. SIG is part of Carnegie Mellon Graphics Lab.

Members

Alumni

Zhitong Cui (Visiting Ph.D. from ZJU), Ruben Partono (CMU MSCS), David Tang (CMU Undergrad)

Opportunities

We are eager to welcome highly motivated and skilled Ph.D. students! If you have a strong background relevant to our research areas and are interested in joining us, you can apply to any of the Ph.D. programs within the School of Computer Science. We recommend prioritizing the Ph.D. in Computer Science program and listing Minchen as a potential advisor. Here are some details about our Ph.D. stipends. Applications with fellowships from external sources are also welcome!

Our group actively invites visiting students and scholars from around the globe to foster interdisciplinary collaborations. Prospective visits usually range between 6 to 12 months. While we provide funding support, candidates are also welcome to explore alternative funds from their home institutions, third-party fellowships, etc. The availability of the positions is limited. If you are interested, please email us with the materials listed here. Students interested in a summer research internship/volunteer [2024 closed] can directly email us their CV, transcripts, and specific research interests aligned with our research focus. We appreciate your understanding that, due to a high influx of emails, we may not be able to respond to all inquiries.

If you are a CMU student interested in working with us, please feel free to forward your CV and specific research interests via email. We strongly recommend embarking on this path by taking foundational and research-focused computer graphics courses, especially 15-462 and 15-769. While our group has limited slots for independent studies and research assistant roles under reduced course load, we remain receptive to diverse forms of collaboration, e.g., SURA, SURF, etc.

We are also open to engaging in collaborations of any kind, both within academia and industry!


A Dynamic Duo of Finite Elements and Material Points

Xuan Li, Minchen Li, Xuchen Han, Huamin Wang, Yin Yang, Chenfanfu Jiang

ACM SIGGRAPH 2024  


VR-GS: A Physical Dynamics-Aware Interactive Gaussian Splatting System in Virtual Reality

Ying Jiang*, Chang Yu*, Tianyi Xie*, Xuan Li* (equal contributions), Yutao Feng, Huamin Wang, Minchen Li, Henry Lau, Feng Gao, Yin Yang, Chenfanfu Jiang

ACM SIGGRAPH 2024  


Mapped Material Point Method for Large Deformation Problems with Sharp Gradients and Its Application to Soil-Structure Interactions

Yidong Zhao, Minchen Li, Chenfanfu Jiang, Jinhyun Choo

International Journal for Numerical and Analytical Methods for Geomechanics (IJNAMG), 2024  


Material Point Methods on Unstructured Tessellations: A Stable Kernel Approach With Continuous Gradient Reconstruction

Yadi Cao, Yidong Zhao, Minchen Li, Yin Yang, Jinhyun Choo, Demetri Terzopoulos, Chenfanfu Jiang

Arxiv 2312.10338  


Power Plastics: A Hybrid Lagrangian/Eulerian Solver for Mesoscale Inelastic Flows

Ziyin Qu, Minchen Li, Yin Yang, Chenfanfu Jiang, Fernando de Goes

ACM Transactions on Graphics (SIGGRAPH Asia), 2023  


Subspace-Preconditioned GPU Projective Dynamics with Contact for Cloth Simulation

Xuan Li, Yu Fang, Lei Lan, Huamin Wang, Yin Yang, Minchen Li, Chenfanfu Jiang

ACM SIGGRAPH Asia 2023  


Neural Stress Fields for Reduced-order Elastoplasticity and Fracture

Zeshun Zong, Xuan Li, Minchen Li, Maurizio M. Chiaramonte, Wojciech Matusik, Eitan Grinspun, Kevin Carlberg, Chenfanfu Jiang, Peter Yichen Chen

ACM SIGGRAPH Asia 2023  


Convergent Incremental Potential Contact

Minchen Li, Zachary Ferguson, Teseo Schneider, Timothy Langlois, Denis Zorin, Daniele Panozzo, Chenfanfu Jiang, Danny M. Kaufman

Arxiv 2307.15908  


Augmented Incremental Potential Contact for Sticky Interactions

Yu Fang*, Minchen Li* (equal contributions), Yadi Cao, Xuan Li, Joshuah Wolper, Yin Yang, Chenfanfu Jiang

IEEE Transactions on Visualization and Computer Graphics (TVCG), 2023  


Multi-Layer Thick Shells

Yunuo Chen, Tianyi Xie, Cem Yuksel, Danny M. Kaufman, Yin Yang, Chenfanfu Jiang, Minchen Li

ACM SIGGRAPH 2023  


A Contact Proxy Splitting Method for Lagrangian Solid-Fluid Coupling

Tianyi Xie, Minchen Li, Yin Yang, Chenfanfu Jiang

ACM Transactions on Graphics (SIGGRAPH), 2023  


Second-order Stencil Descent for Interior-point Hyperelasticity

Lei Lan, Minchen Li, Chenfanfu Jiang, Huamin Wang, Yin Yang

ACM Transactions on Graphics (SIGGRAPH), 2023  


A Sparse Distributed Gigascale Resolution Material Point Method

Yuxing Qiu, Samuel T. Reeve, Minchen Li, Yin Yang, Stuart R. Slattery, Chenfanfu Jiang

ACM Transactions on Graphics, 2022 (presentation at SIGGRAPH 2023)  


Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale GNN

Yadi Cao, Menglei Chai, Minchen Li, Chenfanfu Jiang

International Conference on Machine Learning (ICML), 2023  


Reconfigurable Data Glove for Reconstructing Physical and Virtual Grasps

Hangxin Liu, Zeyu Zhang, Ziyuan Jiao, Zhenliang Zhang, Minchen Li, Chenfanfu Jiang, Yixin Zhu, Song-Chun Zhu

Engineering, 2023  


TPA-Net: Generate A Dataset for Text to Physics-based Animation

Yuxing Qiu, Feng Gao, Minchen Li, Govind Thattai, Yin Yang, Chenfanfu Jiang

Arxiv 2211.13887  


PlasticityNet: Learning to Simulate Metal, Sand, and Snow for Optimization Time Integration

Xuan Li, Yadi Cao, Minchen Li, Yin Yang, Craig Schroeder, Chenfanfu Jiang

Neural Information Processing Systems (NIPS), 2022  


A Unified Newton Barrier Method for Multibody Dynamics

Yunuo Chen*, Minchen Li* (equal contributions), Lei Lan, Hao Su, Yin Yang, Chenfanfu Jiang

ACM Transactions on Graphics (SIGGRAPH), 2022  


Energetically Consistent Inelasticity for Optimization Time Integration

Xuan Li, Minchen Li, Chenfanfu Jiang

ACM Transactions on Graphics (SIGGRAPH), 2022  


Affine Body Dynamics: Fast, Stable & Intersection-free Simulation of Stiff Materials

Lei Lan, Danny M. Kaufman, Minchen Li, Chenfanfu Jiang, Yin Yang

ACM Transactions on Graphics (SIGGRAPH), 2022  


The Power Particle-In-Cell Method

Ziyin Qu, Minchen Li, Fernando de Goes, Chenfanfu Jiang

ACM Transactions on Graphics (SIGGRAPH), 2022  


An Efficient B-Spline Lagrangian/Eulerian Method for Compressible Flow, Shock Waves, and Fracturing Solids

Yadi Cao, Yunuo Chen, Minchen Li, Yin Yang, Xinxin Zhang, Mridul Aanjaneya, Chenfanfu Jiang

ACM Transactions on Graphics, 2022 (presentation at SIGGRAPH 2022)  


A Large-Scale Benchmark for the Incompressible Navier-Stokes Equations

Zizhou Huang, Teseo Schneider, Minchen Li, Chenfanfu Jiang, Denis Zorin, Daniele Panozzo

Arxiv 2112.05309  


A Barrier Method for Frictional Contact on Embedded Interfaces

Yidong Zhao*, Jinhyun Choo* (equal contribution), Yupeng Jiang, Minchen Li, Chenfanfu Jiang, Kenichi Soga

Computer Methods in Applied Mechanics and Engineering (CMAME), 2022  


BFEMP: Interpenetration-Free MPM-FEM Coupling with Barrier Contact

Xuan Li*, Yu Fang* (equal contribution), Minchen Li, Chenfanfu Jiang

Computer Methods in Applied Mechanics and Engineering (CMAME), 2021  


Codimensional Incremental Potential Contact

Minchen Li, Danny M. Kaufman, Chenfanfu Jiang

ACM Transactions on Graphics (SIGGRAPH), 2021  


Guaranteed Globally Injective 3D Deformation Processing

Yu Fang*, Minchen Li* (equal contribution), Chenfanfu Jiang, Danny M. Kaufman

ACM Transactions on Graphics (SIGGRAPH), 2021  


Intersection-free Rigid Body Dynamics

Zachary Ferguson, Minchen Li, Teseo Schneider, Francisca Gil-Ureta, Timothy Langlois,
Chenfanfu Jiang, Denis Zorin, Danny M. Kaufman, Daniele Panozzo

ACM Transactions on Graphics (SIGGRAPH), 2021  


Medial IPC: Accelerated Incremental Potential Contact With Medial Elastics

Lei Lan*, Yin Yang* (equal contribution), Danny M. Kaufman, Junfeng Yao, Minchen Li, Chenfanfu Jiang

ACM Transactions on Graphics (SIGGRAPH), 2021  


Soft Hybrid Aerial Vehicle via Bistable Mechanism

Xuan Li*, Jessica McWilliams* (equal contribution), Minchen Li, Cynthia Sung, Chenfanfu Jiang

IEEE International Conference on Robotics and Automation (ICRA), 2021  

Best Paper Award in Mechanisms and Design


Lagrangian-Eulerian Multi-Density Topology Optimization with the Material Point Method

Yue Li*, Xuan Li*, Minchen Li* (equal contribution), Yixin Zhu, Bo Zhu, Chenfanfu Jiang

International Journal for Numerical Methods in Engineering (IJNME), 2021  


Robust and Accurate Simulation of Elastodynamics and Contact

Minchen Li

Ph.D. Dissertation, University of Pennsylvania, 2020  


Incremental Potential Contact: Intersection- and Inversion-free, Large-Deformation Dynamics

Minchen Li, Zachary Ferguson, Teseo Schneider, Timothy Langlois, Denis Zorin, Daniele Panozzo, Chenfanfu Jiang, Danny M. Kaufman

ACM Transactions on Graphics (SIGGRAPH), 2020  


AnisoMPM: Animating Anisotropic Damage Mechanics

Joshuah Wolper, Yunuo Chen, Minchen Li, Yu Fang, Ziyin Qu, Jiecong Lu, Meggie Cheng, Chenfanfu Jiang

ACM Transactions on Graphics (SIGGRAPH), 2020  


IQ-MPM: An Interface Quadrature Material Point Method for Non-sticky Strongly Two-Way Coupled Nonlinear Solids and Fluids

Yu Fang*, Ziyin Qu* (equal contribution), Minchen Li, Xinxin Zhang, Yixin Zhu, Mridul Aanjaneya, Chenfanfu Jiang

ACM Transactions on Graphics (SIGGRAPH), 2020  


A Massively Parallel and Scalable Multi-GPU Material Point Method

Xinlei Wang*, Yuxing Qiu* (equal contribution), Stuart R. Slattery, Yu Fang, Minchen Li, Song-Chun Zhu, Yixin Zhu, Min Tang,
Dinesh Manocha, Chenfanfu Jiang

ACM Transactions on Graphics (SIGGRAPH), 2020  


Hierarchical Optimization Time Integration for CFL-rate MPM Stepping

Xinlei Wang*, Minchen Li* (equal contribution), Yu Fang, Xinxin Zhang, Ming Gao, Min Tang, Danny M. Kaufman, Chenfanfu Jiang

ACM Transactions on Graphics, 2020 (presentation at SIGGRAPH 2020)  


A Hybrid Material-Point Spheropolygon-Element Method for Solid and Granular Material Interaction

Yupeng Jiang, Minchen Li, Chenfanfu Jiang, Fernando Alonso-Marroquin

International Journal for Numerical Methods in Engineering (IJNME), 2020  


Decomposed Optimization Time Integrator for Large-Step Elastodynamics

Minchen Li, Ming Gao, Timothy Langlois, Chenfanfu Jiang, Danny M. Kaufman

ACM Transactions on Graphics (SIGGRAPH), 2019  


Silly Rubber: An Implicit Material Point Method for Simulating Non-equilibrated Viscoelastic and Elastoplastic Solids

Yu Fang, Minchen Li, Ming Gao, Chenfanfu Jiang

ACM Transactions on Graphics (SIGGRAPH), 2019  


CD-MPM: Continuum Damage Material Point Methods for Dynamic Fracture Animation

Joshuah Wolper, Yu Fang, Minchen Li, Jiecong Lu, Ming Gao, Chenfanfu Jiang

ACM Transactions on Graphics (SIGGRAPH), 2019  


OptCuts: Joint Optimization of Surface Cuts and Parameterization

Minchen Li, Danny M. Kaufman, Vladimir G. Kim, Justin Solomon, Alla Sheffer

ACM Transactions on Graphics (SIGGRAPH Asia), 2018  


FoldSketch: Enriching Garments with Physically Reproducible Folds

Minchen Li, Alla Sheffer, Eitan Grinspun, Nicholas Vining

ACM Transactions on Graphics (SIGGRAPH), 2018  


Resolving Fluid Boundary Layers with Particle Strength Exchange and Weak Adaptivity

Xinxin Zhang, Minchen Li, Robert Bridson

ACM Transactions on Graphics (SIGGRAPH), 2016  


A Tutorial on Backward Propagation Through Time (BPTT) in the Gated Recurrent Unit (GRU) RNN

Minchen Li

Technical Report, 2016  


*Please see Google Scholar for the complete publication list.


Instructor, Carnegie Mellon University

 • 15-362/662: Computer Graphics (Fall 2024)
 • 15-769: Physics-based Animation of Solids and Fluids (Fall 2023, Spring 2025)

Instructor, University of California, Los Angeles

 • Math 164: Optimization (Fall 2022)
 • Math 151A: Applied Numerical Methods (Fall 2021)
 • Math 32A: Calculus of Several Variables (Summer 2021)


Teaching Assistant, University of Pennsylvania

 • EAS 205: Scientific Computing (Spring 2020)
   Instructor: Chenfanfu Jiang
 • CIS 563: Physics-Based Animation (Fall 2019)
   Instructor: Chenfanfu Jiang

Teaching Assistant, University of British Columbia


I love travel, photography, and films.