Faculty Directory
Wei Chen

Chair and Professor of Mechanical Engineering

Wilson-Cook Professor in Engineering Design

Professor of Industrial Engineering and Management Sciences and Materials Science and Engineering (by courtesy)

Contact

2145 Sheridan Road
L293
Evanston, IL 60208-3109

847-491-7019Email Wei Chen

Website

Integrated Design Automation Lab

Departments

Mechanical Engineering

Affiliations

Theoretical and Applied Mechanics Graduate Program

Education

PhD in Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA

MS in Mechanical Engineering, University of Houston, Houston, TX

BS in Mechanical Engineering, Shanghai Jiaotong University, China


Research Interests

Simulation-based design under uncertainty; AI and machine learning for predictive science and engineering design; multifidelity modeling and uncertainty quantification; data-driven design of heterogenous nano- and microstructural materials and programmable metamaterials; digital twins for autonomous manufacturing; topology optimization and co-design of materials and structures; multidisciplinary design optimization; network analysis for modeling consumer preference and decision-based design. Dr. Chen is the Director of the Integrated Design Automation Laboratory (IDEAL) and the Founding Director of the Predictive Science and Engineering Design (PSED) Cluster. Her current research involves the use of statistical inference, machine learning, and uncertainty quantification techniques for adaptive discovery and design of a wide range of emerging materials systems, by integrating knowledge and representation from multiple disciplines and domains such as materials, manufacturing, structural mechanics, data science, and design optimization. Her research methods have been integrated into commercial software and making direct societal impacts through industrial collaborations and applications in developing multifunctional, lightweight, portable, energy efficient, and sustainable materials, products and processes.


Significant Recognition

  • Member of American Academy of Arts and Sciences (AAA&S), elected 2024
  • NSF BRITE Fellow, for research on “AI-Enabled Discovery and Design of Programmable Material Systems”, 2023
  • Engineering Science Medal, Society of Engineering Science, 2022
  • Charles Russ Richards Memorial Award, American Society of Mechanical Engineers (ASME) and Pi Tau Sigma, 2021, to recognize outstanding achievement by an individual who graduated in mechanical engineering more than 20 years ago.
  • Member of National Academy of Engineering (NAE), elected 2019
  • Robert E. Abbott Award, ASME Design Engineering Division (DED), 2019
  • Ver Steeg Faculty Award, The Graduate School, Northwestern University, 2018
  • Design Automation Award, American Society of Mechanical Engineers (ASME), Design Engineering Division, 2015
  • Best Paper Award, ASME Design Automation Conference, 1998, 2012, 2014, 2016, 2019, and 2022
  • Fellow, American Society of Mechanical Engineers (ASME), 2009
  • Ralph R. Teetor Education Award, Society of Automotive Engineering, 2006
  • National Science Foundation Faculty Early Career Award, 1996 - 2001
  • ASME Pi Tau Sigma Gold Medal achievement award, 1998, to recognize outstanding achievement by an individual who graduated in mechanical engineering more than 10 years ago.
  • Sigma Xi Doctoral Dissertation Award, Georgia Tech Chapter, 1996

Significant Professional Service

  • Elected Member (2022-present) and Chair (2025-2026), ASME Mechanical Engineering Department Heads Executive Committee (MEDHEC)
  • Member, National Academies' Board on Mathematical Sciences and Analytics, 2020-present.
  • Past President (2023-2027) and President (2019-2023), International Society of Structural & Multidisciplinary Optimization (ISSMO)
  • Member of ASME Technical Committee Publication Committee (TCPC) (2023-2029)
  • Co-editor, Structural and Multidisciplinary Optimization
  • Editorial Advisory Board, Computer Methods in Applied Mechanics and Engineering
  • Executive Board Member, Machine Learning: Engineering
  • Editorial Board Member, NPJ Metamaterials
  • Editor-in-Chief, ASME Journal of Mechanical Design (2018-2022)
  • Elected Member, Executive Committee of ASME Design Engineering Division (2009-2015); Chair (2013-2014)
  • Elected Member, Advisory Board of the Design Society (2007-2013)
  • Associate Editor, ASME Journal of Mechanical Design (2003-2006; 2010-2013)
  • Associate Editor, SIAM/ASA Journal on Uncertainty Quantification (JUQ) (2015-2017)
  • Department Editor, IIE Transactions (Department on “Design Engineering and Product Realization) (2014-2017)
  • Associate Editor, Engineering Optimization (2007-2009)
  • Associate Editor, Journal of Design and Manufacturing Automation (2000-2003)

Selected Publications


Chen, Y.-P., Karkaria, V., Tsai, Y.-K., Rolark, F., Quispe, D., Gao, R., Cao, J., Chen, W. (2025). Real-Time Decision-Making for Digital Twin in Additive Manufacturing with Model Predictive Control using Time-Series Deep Neural Networks. Journal of Manufacturing Systems, 80. DOI:10.1016/j.jmsy.2025.03.009.


Pandey, A., Chen, Wei, Keten, S. (2025). COLOR: A compositional linear operation-based representation of protein sequences for identification of monomer contributions to properties. ACS Journal of Chemical Information and Modeling. https://doi.org/10.48550/arXiv.2501.06371.


Comlek, Y., Ravi, S.K., Pandita, P., Ghosh, S., Wang, L., and Chen, W. (2025). Heterogeneous Multi-Source Data Fusion Through Input Mapping and Latent Variable Gaussian Process. Journal of Mechanical Design, 147(4): 041711. https://doi.org/10.1115/1.4068016.


Karkaria, V., Tsai, Y-K, Chen, Y-P., and Chen, W. (2025). An Optimization-Centric Review for Integrating Artificial Intelligence and Digital Twin Technologies in Manufacturing. Engineering Optimization. https://doi.org/10.1080/0305215X.2024.2434201.


Chen, W.W., Lee, D., Sun, R., Portela, C., and Chen, W. (2024). Generative Inverse Design of Metamaterials with Functional Responses by Interpretable Learning. Advanced Intelligent Systems. DOI:10.1002/aisy.202400611.


Zhang, H., Lai, T., Chen, J., Manthiram, A., Rondinelli, J. M., and Chen, W. (2024). Learning Molecular Mixture Property Using Chemistry-Aware Graph Neural Network. PRX Energy, 3, 023006. https://doi.org/10.1103/PRXEnergy.3.023006.


Karkaria, V., Goeckner, A., Zha, R., Chen, J., Zhang, J., Zhu, Q., Cao, J., Gao, R.X., and Chen, W. (2024). Towards a Digital Twin Framework in Additive Manufacturing: Machine Learning and Bayesian Optimization for Time Series Process Optimization. Journal of Manufacturing Systems.


Chen, Y.-P., Wang, L., Comlek, Y., and Chen, W. (2024). A Latent Variable Approach for Non-Hierarchical Multi-Fidelity Adaptive Sampling. Computer Methods in Applied Mechanics and Engineering, 421. https://doi.org/10.1016/j.cma.2024.116773.


Lee, D., Zhang, L., Yu, Y., and Chen, W. (2024). Deep Neural Operator Enabled Concurrent Multitask Design for Multifunctional Metamaterials under Heterogeneous Fields. Advanced Optical Materials. DOI:10.1002/adom.202303087.


Lee, D., Chen, W.W., Wang, L., Chan, Y-C., and Chen, Wei. (2023). Data-Driven Design for Metamaterials and Multiscale Systems: A Review. Advanced Materials. https://doi.org/10.1002/adma.202305254.


Wang, L., Chang, Y., Wu, S., Zhao, R.R., and Chen, W. (2023). Physics-aware differentiable design of magnetically actuated kirigami for shape morphing. Nature Communications. https://doi.org/10.1038/s41467-023-44303-x.


Zhang, H., Chen, W.W., Rondinelli, J., and Chen, W. (2023). ET-AL: Entropy-targeted Active Learning for Bias Mitigation in Materials Data. Applied Physics Reviews, 10(2). https://doi.org/10.1063/5.0138913.


Van Beek, A., Karkaria, V., Chen, W. (2023). Digital Twins for the Designs of Systems: a Perspective. Structural and Multidisciplinary Optimization, 66(3). DOI:10.1007/s00158-023-03488-x.


Chen, W.W., Lee, D., Balogun, O., and Chen, W. (2023). GAN-DUF: Hierarchical Deep Generative Models for Design under Free-From Geometric Uncertainty. Journal of Mechanical Design, 145(1). https://doi.org/10.1115/1.4055898.


In the Classroom

Professor Chen has taught the courses: Intro to Mechanical Design and Manufacturing, Engineering Design (Capstone Design), Computational Methods for Engineering Design, Engineering Optimization for Product Design & Manufacturing, and Advanced Computational & Statistical Methods for Engineering Design.

Wei Chen in the News