Projects per year
Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Research Interest Keywords
- Physics-enhanced machine learning
- Data-driven material modeling
- Composite
- Fracture mechanics
- Subsurface flow and transport
- AI in Geoscience
- Soft tissue modeling
- Scientific machine learning
- meshfree methods
- Metamaterials
- computational mechanics
- Reduced-order modeling
- Multiscale modeling
- Topology optimization
- Multiphysics simulation
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Collaborations and top research areas from the last five years
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Microstructure-Informed Neural Multiscale Modeling Framework for Multiphase Soft Composite Systems
He, Q. (PI)
6/1/25 → 6/30/26
Project: Research project
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Using electric vehicle onboard data for pavement quality assessment and management
Marasteanu, M. (PI), He, Q. (CoI) & Stern, R. (CoI)
MINNESOTA DEPARTMENT OF TRANSPORTATION, US DOT FEDERAL HIGHWAY ADMINISTRATION
7/1/23 → 12/31/25
Project: Research project
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Multiphysics Data Assimilation Framework Based on Process-Aware Neural Operator for Failure Prediction in Additive Manufacturing
8/1/22 → 12/31/23
Project: Internal Grant
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Differentiable neural-integrated meshfree method for forward and inverse modeling of finite strain hyperelasticity
Du, H., Guo, B. & He, Q. Z., Jun 2025, In: Engineering with Computers. 41, 3, p. 1597-1617 21 p.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
A multi-resolution physics-informed recurrent neural network: formulation and application to musculoskeletal systems
Taneja, K., He, X., He, Q. Z. & Chen, J. S., May 2024, In: Computational Mechanics. 73, 5, p. 1125-1145 21 p.Research output: Contribution to journal › Article › peer-review
Open Access7 Scopus citations -
Neural-Integrated Meshfree (NIM) Method: A differentiable programming-based hybrid solver for computational mechanics
Du, H. & He, Q. Z., Jul 2024, In: Computer Methods in Applied Mechanics and Engineering. 427, 117024.Research output: Contribution to journal › Article › peer-review
7 Scopus citations -
A coupled reinforcement learning and IDAES process modeling framework for automated conceptual design of energy and chemical systems
Wang, D., Bao, J., Zamarripa-Perez, M. A., Paul, B., Chen, Y., Gao, P., Ma, T., Noring, A. A., Iyengar, A. K. S., Schwartz, D. T., Eggleton, E. E., He, Q., Liu, A., Marina, O. A., Koeppel, B. & Xu, Z., Sep 21 2023, In: Energy Advances. 2, 10, p. 1735-1751 17 p.Research output: Contribution to journal › Article › peer-review
Open Access1 Scopus citations -
A hybrid deep neural operator/finite element method for ice-sheet modeling
He, Q. Z., Perego, M., Howard, A. A., Karniadakis, G. E. & Stinis, P., Nov 1 2023, In: Journal of Computational Physics. 492, 112428.Research output: Contribution to journal › Article › peer-review
Open Access10 Scopus citations