People

Director

• Dr Michel-AlexandreCardin

  

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  Dr Michel-AlexandreCardin Senior Lecturer in Computational Aided Engineering

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  Dyson School of Design Engineering

  Michel-Alexandre is a Senior Lecturer (Associate Professor) in Computational Aided Engineering at the  Dyson School of Design Engineering , and Lead of the Strategic Engineering Lab. 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 flexibility, sustainability and resilience in complex engineered systems, with the goal of improving expected performance in the face of uncertainty and risks. This is highly needed, especially given ongoing and future threats from climate change, cyber and physical terrorism, and pandemics. His latest efforts explore the roles of AI and machine learning as part of this emerging paradigm.

PhD Students

• Cesare Caputo

  

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  Cesare Caputo EPSRC funded PhD Student (Dyson School of Design Engineering)

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  Research Interests

  Cesare is an EPSRC funded doctoral student working on applications of Machine Learning in the design process for energy systems under uncertainty. His work focuses on the integration of flexibility, resilience and sustainability into a unified framework which is better aligned with the United Nations Sustainable Development Goals(UN SDGs) and can be used in the early stages of the design decision making progress. Engineering options theory, stochastic optimization and deep reinforcement learning are some of the core interests guiding the investigation.

• Luka Malone

  

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  Luka Malone PhD Student (Dyson School of Design Engineering)

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  Research Interests

  As a current PhD candidate with Dr Cardin as my supervisor, my work involves analyzing decision making under uncertainty and systems design and analysis in the context of space mining, using virtual reality as a key research tool. 

• Nisha Saduagkan

  

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  Nisha Saduagkan PhD Student (Dyson School of Design Engineering)

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  Research Interests

  Nisha is a PhD candidate with an Aeronautical Engineering background, researching the use of optimisation to improve the performance of design systems under uncertainty. Her research will focus on applying multi-agent reinforcement learning (MARL) to complex systems with multiple decision makers and implementing Flexibility in Design (FiD) to achieve an optimal solution, measured by the system’s sustainability and resilience. 

   This research will be applied to the design of infrastructure for future electric transport, namely airport infrastructure to accommodate future fleets of short-haul eVTOL aircraft for urban point-to-point travel. The combination of MARL and FiD will allow us to plan ahead to achieve a system which will perform efficiently and reliably throughout its life-cycle whilst maintaining a robust and durable way to overcome adverse conditions, and thus quantifiable as sustainable and resilient infrastructure.

• Kosuke Ikeya

  

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  Kosuke Ikeya PhD student (Earth Science and Engineering)

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  Research Interests

  Kosuke Ikeya is a PhD student in Earth Science and Engineering at Imperial College London and has an MSc in Aerospace Engineering from the University of Michigan and an MEng in Engineering Sciences and Design from Tokyo Institute of Technology. His research at Imperial supervised by Dr M.-A. Cardin and Professor  J. Cilliers  focuses on Space Resource Utilisation (SRU), also known as In-Situ Resource Utilisation (ISRU), on the moon. Specifically, he tackles the challenge of optimising SRU plants' design and their deployment strategies considering uncertain parameters in the lunar environment (e.g. particle sizes of the lunar soil, regolith) and space mission operation (e.g. rocket launch failure).