Design by Data: Cultivating Datasets for Engineering Design

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.

Cyril Picard

Cyril Picard is a Swiss National Science Foundation Postdoctoral Fellow at the Massachusetts Institute of Technology (MIT). He received is B.Sc., M.Sc., and Doctor of Science, all in Mechanical Engineering from EPFL (École polytechnique fédérale de Lausanne). His research is focused on exploring the use of machine learning to support the design of complex mechanical systems.

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.

Faez Ahmed

Faez Ahmed is an assistant professor in the Department of Mechanical Engineering at MIT, where he leads the Design Computation and Digital Engineering (DeCoDE) lab. His research focuses on developing new machine learning and optimization methods to study complex engineering design problems. His recent work includes proposing automated design synthesis methods to generate novel high-performance designs, creating the first provably optimal algorithm for the diverse matching problem, and building computationally efficient ways for combining physics with human expert knowledge to design new products. Before joining MIT, Ahmed was a postdoctoral fellow at Northwestern University and completed his PhD in mechanical engineering at the University of Maryland. He also worked in the railway and mining industry in Australia, where he pioneered data-driven predictive maintenance and renewal planning efforts.

Christopher McComb

Christopher McComb is an Associate Professor in the Department of Mechanical Engineering at Carnegie Mellon University. He received dual B.S. degrees in Civil and Mechanical Engineering from California State University-Fresno in 2012. Later he attended Carnegie Mellon University as a National Science Foundation Graduate Research Fellow and obtained his M.S. and Ph.D. in Mechanical Engineering in 2014 and 2016, respectively. His research expertise is in design computation, with specific focuses on machine learning for engineering design, agent-based modeling of human systems, and human-AI collaboration. Application areas include design for additive manufacturing, marine energy devices, and drone delivery systems.

Pingfeng Wang

Pingfeng Wang is an Associate Professor in the Department of Industrial and Enterprise Systems Engineering at University of Illinois at Urbana-Champaign (UIUC), and the director of the Reliability Analysis and Safety Assurance (RASA) lab at Illinois. He received his B.S. in 2001 in Mechanical Engineering from University of Science and Technology in Beijing, his M.S. in 2006 in Applied Math from Tsinghua University, and his Ph.D. in 2010 in Mechanical Engineering from University of Maryland. Dr. Wang’s research has been focused on developing new design methods and tools to improve reliability, safety and failure resilience of engineered systems. He is the recipient of the NSF CAREER award (2014), the Young Researcher Award from International Society of Green Manufacturing and Applications (2012), the ASME Design Automation Young Investigator Award (2016), and Best Paper Awards in the ASME Design Automation Conferences (2008 and 2013).

Ikjin Lee

Dr. Ikjin Lee is an associate professor of Mechanical Engineering at Korea Advanced Institute of Science and Technology (KAIST).

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Areas: Design by Data: Cultivating Datasets for Engineering Design