Michel-Alexandre is an Associate Professor (Senior Lecturer in the UK) in Computational Aided Engineering at the Dyson School of Design Engineering, Imperial College London. He is Lead of the Strategic Engineering Laboratory.
Broadly speaking, he works on Systems Design and Optimization under Uncertainty, focusing on the development and evaluation of new computational techniques, digital processes, and algorithms to support the design of complex engineered systems, with applications in energy, transportation, and space systems. The work covers methodological topics such as concept generation and selection, decision-making under uncertainty, machine learning, stochastic optimization, uncertainty modeling, and virtual/augmented reality.
An important theme in the research is the concept of Flexibility in Engineering Design. This paradigm emerged from the theory of Real Options and seeks to design complex systems that adapt, reconfigure and change in the face of uncertainty and risks, with the goal of improving economic performance, sustainability, and resilience. Research on this emerging paradigm is highly needed, especially given ongoing threats from climate change, healthcare emergencies, geo-political tensions, and cyber-physical terrorism. Latest efforts focus on the development of a theory for Data-Driven Systems Design for Uncertainty, which explores the roles of AI and machine learning as part of this emerging paradigm.
Prior to joining Imperial College, Dr. Cardin served as a faculty member at the National University of Singapore (2011-2018), where he established the Strategic Engineering Laboratory. He worked as a Quantitative Researcher in the hedge fund industry, developing systematic strategies for derivatives trading using machine learning. He was a principal investigator for the Singapore-ETH Centre Future Resilient Systems project, and the Singapore-MIT Alliance for Research and Technology.
Dr. Cardin holds a PhD in Engineering Systems and a Master of Science in Technology and Policy from MIT, a Master of Applied Science in Aerospace Engineering from the University of Toronto, Honors BSc in Physics from McGill University in Canada, and is a graduate of the Space Science Program at the International Space University. He is currently serving as Associate Editor for the ASME Journal of Mechanical Design, served as Associate Editor for the INCOSE journalSystems Engineering (2013-2021), and on the Editorial Review Board for the journal IEEE Transactions on Engineering Management (2013-2019). He is an avid ice hockey player, and proud father of three.
Caputo C, Cardin MA, 2022, Analyzing Real Options and Flexibility in Engineering Systems Design Using Decision Rules and Deep Reinforcement Learning, Journal of Mechanical Design, Vol:144, ISSN:1050-0472
Caunhye AM, Cardin M-A, 2017, An approach based on robust optimization and decision rules for analyzing real options in engineering systems design, Iise Transactions, Vol:49, ISSN:2472-5854, Pages:753-767
et al., 2017, An approach for analyzing and managing flexibility in engineering systems design based on decision rules and multistage stochastic programming, Iise Transactions, Vol:49, ISSN:2472-5854, Pages:1-12
Cardin MA, 2014, Enabling flexibility in engineering systems: A taxonomy of procedures and a design framework, Journal of Mechanical Design, Vol:136, ISSN:1050-0472
et al., 2013, Empirical evaluation of procedures to generate flexibility in engineering systems and improve lifecycle performance, Research in Engineering Design, Vol:24, ISSN:0934-9839, Pages:277-295