Dr Namhoon Cho

Areas of expertise

• Aeronautical Systems
• Autonomous Systems
• Computing, Simulation & Modelling
• Defence Systems Engineering
• Flight Physics
• Mechatronics & Advanced Controls
• Operational Analysis and Simulation
• Space Systems
• Weapons Engineering

Background

Namhoon Cho is Lecturer in Control and Optimisation in the Centre for Assured and Connected Autonomy, Faculty of Engineering and Applied Sciences, Cranfield University, United Kingdom, since November 2024. He received his BSc and PhD degrees in Mechanical and Aerospace Engineering from Seoul National University, South Korea, in August 2012 and February 2017, respectively. Previously, he was a research fellow at Cranfield University from January 2021 to November 2024 with the award of a Cranfield 75th Anniversary Fellowship to pursue research on AI for Exploitation of Data-Driven Approach in Control for Aerospace Systems. He was a senior researcher in the 1st R&D Institute, Agency for Defense Development, South Korea, from March 2019 to December 2020, where he was involved in research and development of guidance and control systems for missiles and developed design tools based on optimisation techniques. He was a research fellow in the Department of Mechanical and Aerospace Engineering, Seoul National University, South Korea, from March 2017 to February 2019. He develops constructive methodologies for the design and analysis of control and estimation systems, with a particular emphasis on autonomous aerospace vehicles. His research interests include coherent integration of learning and control on the basis of optimisation, robust adaptive control methods based on online model learning, applications of machine learning algorithms to problems in control and estimation, data-driven safe control frameworks, unified frameworks for automated design of optimal guidance and control systems, and online trajectory optimisation.

Research opportunities

Recipient of 75th Anniversary Research Fellowship at Cranfield University, seeking new possibilities of emerging technological paradigms when combined with the understandings provided by control theory.

As a researcher in autonomy and control primarily for aerospace systems, I lead fundamental and applied research to develop constructive design frameworks for control and machine learning algorithms, which will potentially enable scalable automated design of intelligent controllers. Since mathematical optimisation lays the theoretical as well as methodological foundation of both control and machine learning, this work particularly focuses on their systematic integration by formulating suitable optimisation problems and by developing problem-tailored optimisation solvers. The core components of my research include: (1) Studying the foundations of optimisation in control and deep learning, (2) Establishing unifying frameworks of convex optimisation algorithms, (3) Developing algorithms for real-time adaptation of control systems, (4) Investigating principled approaches to utilise deep neural network models for robust control.

Robust adaptive control

Convex optimisation

Machine learning for control and estimation

Optimisation for deep learning

Machine learning for optimisation

Guidance, navigation, and control (GNC)

Safe learning and control

Control design automation

Applications to autonomous aerospace systems

Current activities

EPSRC IAA ECR Exploratory Impact Award: Implementation of Advanced Adaptive Control Algorithms for Aerospace Applications | March 2024 - December 2024 | PI | Research project funded by Cranfield University block funding

Flight Control Technologies - Control Allocation Algorithms: Understanding the State of the Art and Future Development Opportunities | September 2022 - November 2022 | Co-I | Research project funded by BAE Systems

AI for Exploitation of Data-Driven Approach in Control for Aerospace Systems | January 2021 - January 2024 | PI | Main research programme for the Cranfield 75th Anniversary Fellowship

Clients

• BAE Systems PLC

Publications

• Articles in journals
• Conference papers
• Books