Michel-Alexandre is a Senior Lecturer (Associate Professor) in Computational Aided Engineering at the Dyson School of Design Engineering. His work focuses on the development and evaluation of new computer aided methodologies to support the design of engineering systems, with applications in infrastructure and financial systems. The work covers topics such as concept generation and selection, decision-making, machine learning, stochastic optimization, and uncertainty modeling.
In particular, his work focuses on design for flexibility (also known as real options), a design paradigm aiming at enabling better adaptability and resilience in complex engineered systems, with the goal of improving expected performance in the face of uncertainty and risks. His latest efforts explore the roles of AI and machine learning as part of this emerging paradigm.
Prior to joining Imperial College, Michel-Alexandre was a faculty member at the National University of Singapore, and worked as a Quantitative Researcher in derivatives trading in the hedge fund industry. He 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, and Honors BSc in Physics from McGill University in Canada. He is also a graduate from the Space Science Program at the International Space University.
Zhao S, Haskell WB, Cardin M-A, 2018, Decision rule-based method for flexible multi-facility capacity expansion problem, Iise Transactions, Vol:50, ISSN:2472-5854, Pages:553-569
Cardin M-A, Zhang S, Nuttall WJ, 2017, Strategic real option and flexibility analysis for nuclear power plants considering uncertainty in electricity demand and public acceptance, Energy Economics, Vol:64, ISSN:0140-9883, Pages:226-237
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 M-A, Hu J, 2016, Analyzing the Tradeoffs Between Economies of Scale, Time-Value of Money, and Flexibility in Design Under Uncertainty: Study of Centralized Versus Decentralized Waste-to-Energy Systems, Journal of Mechanical Design, Vol:138, ISSN:1050-0472
et al., 2015, Training Design and Management of Flexible Engineering Systems: An Empirical Study Using Simulation Games, Ieee Transactions on Systems Man Cybernetics-systems, Vol:45, ISSN:2168-2216, Pages:1268-1280
Hu J, Cardin M-A, 2015, Generating flexibility in the design of engineering systems to enable better sustainability and lifecycle performance, Research in Engineering Design, Vol:26, ISSN:0934-9839, Pages:121-143
Cardin M-A, 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