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 work focuses on advancing data-enhanced numerical methods, scientific machine learning and data assimilation to simulate, optimize, and control a wide range of multiscale and multiphysics problems.
Our main research themes include:
1) Investigate multiphysics phenomena and damage mechanism in heterogeneous porous media and composite materials by developing novel computational techniques, such as data-driven constitutive modeling, meshfree methods, multiscale simulations, and physics-informed machine learning.
2) Develop next-generation computational methods and algorithms for Software 2.0 to enable high-performance computing with integrated data assimilation and AI capabilities.
3) Advance the knowledge of scientific machine learning and reduced-order modeling for large-scale simulation and inverse problems, with applications to natural hazard mitigation, earth science, energy storage, and meta-material design.
For more information about our active research, see Research and Publication.
Recent News
- 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]