Design by Data: Cultivating Datasets for Engineering Design

Leifur Leifsson

Leifur Leifsson is an Associate Professor with the School of Aeronautics and Astronautics at Purdue University, West Lafayette, Indiana. He received his undergraduate and master’s degrees in mechanical engineering from the University of Iceland, and a PhD degree in aerospace engineering from Virginia Tech. Prior to coming to Purdue, he worked at Airbus UK as a wing integration engineer, and he was an Associate Professor at the Department of Aerospace Engineering at Iowa State University, Ames, Iowa. At Purdue, his current research focuses on advancing fundamental computational methods for multidisciplinary design optimization, surrogate-based modeling and optimization, reduced-order modeling, multifidelity modeling, sampling, and uncertainty quantification. Application areas include aerodynamic shape optimization, aerothermodynamics modeling, aircraft design, and microwave systems design and optimization. Leifsson currently serves as an Associate Editor of the AIAA Journal. He is a member of the AIAA Multidisciplinary Design Optimization Technical Committee.

Kathryn Maupin

Kathryn Maupin is a Principal Member of the Technical Staff at Sandia National Laboratories. Motivated by a passion for transforming uncertainty into actionable insights, Kathryn leverages her extensive expertise in model validation, model form error quantification, and Bayesian analyses to drive innovative solutions that enhance research outcomes. Kathryn earned her PhD in Computational Science, Engineering, and Mathematics, along with her M.S. in Computational and Applied Mathematics, both from The University of Texas at Austin. Her fascination with mathematical modeling began at the University of California, San Diego, where she completed her B.A. in Applied Mathematics. When she is not immersed in data and algorithms, Kathryn enjoys the chaos of family life with her three children and three dogs. Looking ahead, Kathryn aspires to continue pushing the boundaries of computational science while encouraging others to confront ubiquitous uncertainty in their work.

Subhayan De

Dr. Subhayan De is an Assistant Professor in the Department of Mechanical Engineering at Northern Arizona University (NAU). He earned his Ph.D. in Civil Engineering in 2018 and M.S. in Electrical Engineering in 2016 from the University of Southern California (USC), supported by a Viterbi Ph.D. Fellowship and a Gammel Scholarship. At NAU, Dr. De leads a research lab dedicated to developing probabilistic, data-driven frameworks that leverage machine learning to efficiently create and validate models aimed at supporting the design of multi-scale, multi-functional structural systems and materials under uncertainty.

Zhen Hu

Dr. Zhen Hu is an associate professor in Department of Industrial and Manufacturing Systems Engineering at the University of Michigan-Dearborn (UM-Dearborn). He received his Ph.D. (2014) in Mechanical Engineering from Missouri University of Science and Technology, Rolla, Missouri, USA. His research interests include design under uncertainty, uncertainty quantification, prognostics and health management, Bayesian data analytics, structural health monitoring, and additive manufacturing. He is a review editor of the Structural and Multidisciplinary Optimization Journal and an associate managing editor of ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering. He is the recipient of 2023 ASME Design Automation Young Investigator Award and a recipient of the 2023 UM-Dearborn CECS Faculty Research Excellent Award.

Ramin Bostanabad

Ramin Bostanabad is a faculty in the Mechanical and Aerospace Engineering Department at the University of California, Irvine (UCI). He is an editorial board member of the Structural and Multi-disciplinary Optimization (SMO) journal and the recipient of 2021 NASA Early Career faculty and 2023 NSF CAREER awards. Dr. Bostanabad earned his Ph.D. in 2019 from Northwestern University where his works were recognized with a number of awards including Terminal Year Fellowship, Martin Outstanding doctoral Fellowship, Predictive Science and Engineering Design Fellowship, and Walter P. Murphy Fellowship. At UCI, his group’s research area is at the interface of design under uncertainty, uncertainty quantification, scientific machine learning, and data-driven computational mechanics.

Stefan Menzel

Stefan Menzel is a Chief Scientist with the Optimization and Creativity Group at the Honda Research Institute Europe, Offenbach, Germany. He received a Dipl.-Ing. degree in civil engineering from RWTH Aachen University, Aachen, Germany, and a Ph.D. degree in civil engineering from Technical University Darmstadt, Darmstadt, Germany. His current research interests include evolutionary optimization with special focus on adaptive representations, machine learning for knowledge transfer, and multidisciplinary optimization for real-world applications.

Tino Stankovic

Tino Stankovic is a senior scientist at Engineering Design and Computing Laboratory at ETH Zürich in Switzerland. His research focuses on developing computational models, methods and tools to support the design for additive manufacturing as well as design optimization, and design automation. Current interests include development of advanced computational design methods to automatically generate and optimize lattice structures, computational design of origami-adapted rigid-foldable structures, and computational design of 3D printed, personalized medical devices. Tino Stankovic serves as a reviewer for several established scientific journals and conferences. He is a member of the Design Society.

Wei Chen

Dr. Wei Chen is the Wilson-Cook Professor in Engineering Design and Chair of Department of Mechanical Engineering at Northwestern University. She received her Ph.D. from the Georgia Institute of Technology, M.S. from University of Houston, and B.S. from Shanghai Jiao Tong University (China), all in mechanical engineering. Dr. Chen is an elected member of the National Academy of Engineering (NAE) and fellow of ASME. She currently serves as the President of the International Society of Structural and Multidisciplinary Design (ISSMO). In the past, she served as a member then Chair of the ASME Design Engineering Division (DED) Executive Committee and was an elected Advisory Board member of the Design Society. Before becoming the editor-in-chief of JMD, Dr. Chen was the Associate Editor of the JMD, Design Science, and the SIAM/ASA Journal on Uncertainty Quantification (JUQ). She also served as the Review Editor of the Structural and Multidisciplinary Optimization (SMO) and the Department Editor for the IIE Transactions. Dr. Chen was the recipient of the joint ASME and Pi Tau Sigma Charles Russ Richards Memorial Award (2021), ASME Robert E. Abbott Award ( 2019) for life time service, ASME Design Automation Award (2015), Intelligent Optimal Design Prize (2005), ASME Pi Tau Sigma Gold Medal achievement award (1998), and the NSF Faculty Career Award (1996). Her research team has received five ASME Design Automation Conference Best Paper Award (2019, 2016, 2014, 2012, and 1998) and the JMD Editors’ Choice Award (2014).

Michael Kokkolaras

Dr. Kokkolaras is Professor, and the founding director of the Systems Optimization Laboratory, at McGill University’s Department of Mechanical Engineering. He received his diploma in Aerospace Engineering from Technische Universität München and his Ph.D. in Mechanical Engineering from Rice University. He is currently serving as the Associate Dean for Faculty Affairs at the Faculty of Engineering. Dr. Kokkolaras joined McGill from the University of Michigan at Ann Arbor (UM), where he held research faculty appointments at the Department of Mechanical Engineering (primary) and the UM Transportation Research Institute (joint/courtesy); he is a recipient of the UM College of Engineering Outstanding Research Scientist Award. Dr. Kokkolaras is an ASME Fellow and is currently serving as Publications Chair of the ASME Design Engineering Division and has previously served as Chair of the Design Automation Executive Committee of the ASME Design Engineering Division, Program and Conference Chair of the ASME Design Automation Conference, and Program Co-Chair of the International Conference on Engineering Design.

Douglas Allaire

Dr. Douglas Allaire is an Associate Professor and Sallie and Don Davis ’61 Faculty Fellow in the J. Mike Walker ’66 Department of Mechanical Engineering at Texas A&M University where he directs the Computational Design Lab (CDL). He holds B.S., M.S., and Ph.D. degrees from the Department of Aeronautics and Astronautics at the Massachusetts Institute of Technology. His current research focuses on the development of computational methods for the analysis, design, and operation of complex systems. He is specifically interested in uncertainty quantification, multidisciplinary design optimization, and machine learning and has recently applied his research to unmanned aerial vehicle systems and the design and discovery of advanced materials. He is the recipient of several awards, including the 2018 ASME Computers and Information in Engineering Division Young Engineer Award and the ASME DAC Best Paper award in 2018.

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