Overview
"Scientists study the world as it is; engineers create the world that never has been."
- Theodore von Kármán
Welcome to the Computational Intelligence and Multiphysics Simulation (CIMS) Lab at the University of Minnesota! We are a multidisciplinary research team that leverages Computational Mechanics, Scientific Computing, and Artificial Intelligence (AI) to address resilience and sustainability challenges related to materials, structures, and geosystems under extreme conditions. Our research advances data-enabled computational methods, including meshfree methods, reduced-order modeling, scientific machine learning, and data assimilation, for the simulation, optimization, and control of complex multiscale and multiphysics systems.
Our research is centered on three core themes:
- Differentiable and AI-Enhanced Scientific Computing
- Multiscale Mechanics of Geological, Composite, and Energy Materials
- Digital Twins and Inverse Modeling for Multiphysics Processes in Subsurface Science and Extreme Hazard Events
For more information about our active research, see Research and Publication.
Recent News
- 05/2026 Short Course: Profs. WaiChing Sun, Nick Vlassis, JS Chen, and I will teach the fifth version of our short course Machine Learning for Solid Mechanics at WCCM-ECCOMAS 2026 Munich on July 19th, July 2016. We will cover selected topics in generative AI, LLMs, geometric learning, and the use of coding agents (Claude, Codex, and other open-source alternatives) for computational mechanics. Due to space constraints, we can only accept 40 registrations. The registration deadline is June 10, 2026. Please feel free to share this announcement with students, colleagues, and others who may be interested. [Link]
- 05/2026 News: Congratulations to Binyao on successfully passing the Preliminary Oral Exam—excited to see you move on to the next milestone.
- 04/2026 Talk: Dr. He delivered an ISRM AI Café Talk titled “Hybrid ML–Physics Forward and Inverse Modeling of Geomechanics and Geophysical Flow Hazards,” organized by the International Society for Rock Mechanics and Rock Engineering. Thanks for the hosting by Hongkyu and Lina, and the invitation from Wei; It was a productive discussion.
- 04/2026 Paper: Congratulations to Honghui on the acceptance of the paper “JAX-MPM: A Learning-Augmented Differentiable Meshfree Framework for GPU-Accelerated Lagrangian Simulation and Geophysical Inverse Modeling” for publication in Engineering with Computers [Link].
- 03/2026 News: Our CIMS group receives a Seed Grant from National Security Research Institute (NSRI) to advance generative Bayesian learning for complex flow dynamics, in collaboration with the Stochastic Hypersonics Research Group led by Prof. del Val (AEM). We sincerely thank NSRI for their support.
- 02/2026 Conference: We are pleased to invite submissions to our mini-symposium:
- "MS 208 - Data-Driven Approaches for Solid Mechanics" at the 20th U.S. National Congress of Theoretical and Applied Mechanics (USNC-TAM 2026), June 21–25, 2026, Pasadena, California
- "MS426 – Data-driven Approaches in Mechanics" at the 17th World Congress on Computational Mechanics (WCCM), 19 - 24 July 2026, Munich, Germany.
- 01/2026 News: Congratulations to Zihan on passing the Preliminary Written Exam!
- 01/2026 Conference: Dr. He will serve as a co-chair of Session IS01 "AI/ML Applications in Rock Mechanics" at the 60th U.S. Rock Mechanics / Geomechanics Symposium of the American Rock Mechanics Association (ARMA), to be held in Tucson, Arizona, USA, on June 21–24, 2026.
- 12/2025 Paper: New paper on arXiv: Differentiable Inverse Modeling with Physics-Constrained Latent Diffusion for Heterogeneous Subsurface Parameter Fields (arXiv:2512.22421, Dec. 27, 2025)
- 12/2025 News: Congratulations to Honghui on passing the Preliminary Oral Exam!
- 10/2025 News: Dr. He has been appointed as a member of the Editorial Board of Acta Mechanica Sinica.
- 09/2025 News: Welcome Niketha (MS student in Computer Science) to the CIMS Lab!
- 09/2025 Paper: Our collaborative paper with PNNL, titled "Integrating Physics-Informed and Data-Driven Neural Networks into Earth System Models: A Comparative Study for Compound Flood Simulation at River-Ocean Interfaces" has been accepted for publication accepted by Journal of Geophysical Research: Machine Learning and Computation. Congratulations to the team!
- 09/2025 Paper: Binyao's paper "History-Aware Neural Operator (HANO)" has been accepted for publication in Computer Methods in Applied Mechanics and Engineering. This study introduces and verifies a novel idea for robust data-driven modeling of generic path-dependent materials (e.g., geomaterials and damaged alloys) through learning from historical loading data while bypassing the need for constructing unphysical internal variable.
- 08/2025 Media Highlight: A 3M collaborative research project led by the CIMS Lab was recently featured in the University of Minnesota News: [Research & Innovation Office] [CEGE].
- 08/2025 Conference: We successfully concluded the workshop GenAI4Science: Integrating Scientific Knowledge into Generative AI at UMN (Aug 13–14, 2025). Dr. He delivered a featured talk on Physics-Constrained Differentiable Modeling and Inverse Design with Latent Machine Learning and also served as a panelist in the GenAI in Materials session. The workshop was recorded and shared on the DSI YouTube channel..
- 08/2025 Education: We successfully hosted an fantastic lecture on Physical AI in Engineering Science and hands-on computer labs as part of our STEM summer program, engaging 20 motivated high school students. Special thanks to our PhD students Binyao and Zihan for their excellent preparation of codes and demonstrations that made the event memorable!
- 07/2025 Conference: The CIMS Lab has three presentations at USNCCM-18 in Chicago, July 20–24, showcasing Advances in Differentiable and AI-Augmented Mechanics [News]:
- Guo, Binyao et al., Attention-Enhanced Fourier Neural Operators for Robust Constitutive Modeling of History-Dependent Nonlinear Materials [Abstract]
- Lin, Zihan et al., A Latent Diffusion Model-Coupled Differentiable Physics Simulator for Inverse Modeling of Heterogeneous Media [Abstract]
- Du, Honghui et al., A Differentiable Meshfree Method for Nonlinear Mechanics and Geomechanics Modeling [Abstract]
- 07/2025 Paper: Two recent preprints:
- 05/2025 Conference: Dr. He presented recent advancements in a differentiable Eulerian–Lagrangian framework (JAX-MPM) for nonlinear mechanics and landslide hazard modeling at the 2025 ASCE Engineering Mechanics Institute (EMI) Conference.
- 05/2026 Upcoming Event: We welcome you to participate in our mini-symposium, "Advancements of Data-Driven Methods in Computational Mechanics" (Mini-Symposia Code: v2vyb), co-organized by Professors Nikolaos Vlassis, Jiun-Shyan Chen, WaiChing Sun, and myself. The symposium will take place at the 2025 ASCE Engineering Mechanics Institute (EMI) Conference in Anaheim, California, from May 27–30, 2025.
- 03/2025 News: Our group receives 3M Research Grant to advance generative AI for polymer discovery. We sincerely thank 3M and our collaborators for their generous support. [News]
- 01/2025 Talk: Dr. He delivered a Seminar in the Department of Aerospace Engineering and Mechanics on the topic of Differentiable Computational Mechanics. [News]