Minchen Li (original) (raw)
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 Physics-Based 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 since 2023. Previously, he was an Assistant Adjunct Professor at the UCLA Department of Mathematics, within the AIVC Lab. He completed his Ph.D. in 2020 from the SIG Center for Computer Graphics at the University of Pennsylvania, advised by Chenfanfu Jiang. Minchen's research accomplishments have been recognized with several prestigious awards, including the SCA Early Career Researcher Award (2024), the ACM SIGGRAPH Outstanding Doctoral Dissertation Award (2021), etc. He is an active member of the research community, regularly serving as a program committee member for conferences such as ACM SIGGRAPH, Eurographics, SCA, and CGI, as well as an external reviewer for journals including ACM TOG, IEEE TVCG, and IEEE ICRA.
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 physics-based 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
- Minchen Li (Principal Investigator)
- Christina Contreras (Administrative Support)
- Guying Lin (CMU Ph.D. student)
- Juntian Zheng (CMU Ph.D. student)
- Michael Liu (Incoming CMU Ph.D. student)
- Zhaofeng Luo (Incoming CMU Ph.D. student)
- Yihao Shi (Visiting Research Assistant, Ph.D. student at ZJU)
- Qirui Fu (Graduate Intern from UPenn)
- Trey Dubose (CMU Undergrad)
- Hanke Chen (CMU Undergrad)
Alumni
Michael Liu (Visiting Research Assistant, Undergrad from UMich),Kevin You (CMU Undergrad), Justin Soza Soto (CMU MSME student),Kemeng Huang (Visiting Research Assistant, Ph.D. student at HKU), Bowen Ren (Undergrad Intern from THU),Zhaofeng Luo (Undergrad Intern from PKU),Yuqi Meng (Undergrad Intern from UMich),Huancheng Lin (Visiting Research Assistant, Ph.D. student at HKU),Zhitong Cui (Visiting Research Assistant, Ph.D. student at ZJU), Ruben Partono (CMU MSCS student), 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 extremely 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. As we can only fund a limited number of visitors, candidates are encouraged 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 can directly email us within February and send 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, we strongly recommend embarking on this path by taking foundational and research-focused computer graphics courses, especially 15-362 and 15-763. In 15-763, you will primarily work on a research-oriented course project focused on physics-based simulation, which can be combined with your own research. For undergrads and MS students, collaboration opportunities include independent studies, thesis projects, and summer internships through programs such as SURA and SURF, as dedicated time commitments are essential for successful research. Due to the limited number of positions in our group, we prioritize students who demonstrate outstanding performance in 15-763.
We are also open to engaging in collaborations of any kind, both within academia and industry!
VR-Doh: Hands-on 3D Modeling in Virtual Reality
Zhaofeng Luo*, Zhitong Cui* (equal contributions), Shijian Luo, Mengyu Chu, Minchen Li
ACM Transactions on Graphics (SIGGRAPH), 2025
CK-MPM: A Compact-Kernel Material Point Method
Michael Liu, Xinlei Wang, Minchen Li
ACM Transactions on Graphics (SIGGRAPH), 2025 code coming soon!
StiffGIPC: Advancing GPU IPC for Stiff Affine-Deformable Simulation
Kemeng Huang, Xinyu Lu, Huancheng Lin, Taku Komura, Minchen Li
ACM Transactions on Graphics, 2025 (presentation at SIGGRAPH 2025) code coming soon!
Barrier-Augmented Lagrangian for GPU-based Elastodynamic Contact
Dewen Guo, Minchen Li, Yin Yang, Sheng Li, Guoping Wang
ACM Transactions on Graphics (SIGGRAPH Asia), 2024
Physics-based Simulation
Minchen Li, Chenfanfu Jiang, Zhaofeng Luo
A Dynamic Duo of Finite Elements and Material Points
Xuan Li, Minchen Li, Xuchen Han, Huamin Wang, Yin Yang, Chenfanfu Jiang
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
Unstructured Moving Least Squares Material Point Methods: A Stable Kernel Approach with Continuous Gradient Reconstruction on General Unstructured Tessellations
Yadi Cao, Yidong Zhao, Minchen Li, Yin Yang, Jinhyun Choo, Demetri Terzopoulos, Chenfanfu Jiang
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
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
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
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
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
TPA-Net: Generate A Dataset for Text to Physics-based Animation
Yuxing Qiu, Feng Gao, Minchen Li, Govind Thattai, Yin Yang, Chenfanfu Jiang
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
A Barrier Method for Frictional Contact on Embedded Interfaces
Yidong Zhao*, Jinhyun Choo* (equal contributions), 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 contributions), 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 contributions), 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 contributions), 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 contributions), 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 contributions), 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 contributions), 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 contributions), 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 contributions), 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
*Please see Google Scholar for the complete publication list.
Instructor, Carnegie Mellon University
• 15-369/669: Numerical Computing (Fall 2025)
• 15-362/662: Computer Graphics (Fall 2024)
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)
• CIS 563: Physics-Based Animation (Fall 2019)
Teaching Assistant, University of British Columbia
I love travel, photography, and films.
