Will Midgley

Dr. Will Midgley is a Senior Lecturer in Mechatronics and Robotics within the School of Mechanical and Manufacturing Engineering at the Faculty of Engineering, UNSW Sydney. His research focuses on applying control engineering principles to address critical challenges in transport decarbonization and vehicle systems optimization.

His educational background includes:

• PhD from Cambridge University

Dr. Midgley's research interests span multiple domains at the intersection of mechanical engineering, control systems, and artificial intelligence. He specializes in mechatronic systems design, robotics applications for transport, and advanced control techniques for reducing emissions from heavy goods vehicles and rail systems. His work integrates applied machine learning and deep learning approaches to solve real-world engineering challenges, particularly in vehicle safety applications and property estimation through machine vision. A significant portion of his research focuses on electric vehicle control systems and the decarbonization of transportation networks, addressing one of the most pressing environmental challenges of our time.

Dr. Midgley has received several prestigious awards recognizing his contributions to engineering research:

• IMechE T A Stewart-Dyer Prize/Frederick Harvey Trevithick Prize for "the most meritorious paper on the subject of railway engineering" (2022)
• Fellowship of the Higher Education Academy (now AdvanceHE) (2020-)
• Best Poster Award, Intelligent Fluid Power Transmission and Control, University of Bath (2019)
• 2012 SAGE Highly Commended Paper for "Comparison of regenerative braking technologies for heavy goods vehicles in urban environments" (2013)

Dr. Midgley has secured significant research funding for his innovative projects, including "Don't Forget the Mortar! A New Approach to Engineering Education" (£65,000, Royal Academy of Engineering, 2022-23), "Optimisation of Intermittent Electrification of Rail Transport for Near-Term Decarbonisation" (£37,000, DTE Network+, 2021-22), "Tyre-Road Friction Estimation using Maximum Entropy" (£24,000, EPSRC, 2021-22), and "Decarbonising High-Speed Bi-Mode Railway Vehicles through Optimal Power Control" (£158,000, RSSB, 2019-20). His research program demonstrates a strong commitment to translating theoretical advances into practical solutions for sustainable transportation.

Dr. Midgley maintains an active research group focused on mechatronics, robotics, and applied machine learning, supervising students in areas of applied control, applied mechatronics, and applied machine learning. His international research experience includes work at Mitsubishi Heavy Industries in Japan and Loughborough University in the UK before joining UNSW Sydney.