Areas of expertise

  • Aeronautical Systems
  • Engines, Powertrains & Alternative Fuels
  • Industrial Automation
  • Instrumentation, Sensors and Measurement Science
  • Mechatronics & Advanced Controls
  • Sensor Technologies
  • Systems Engineering
  • Through-life Engineering Services
  • Vehicle Health Management


Professor Starr was Head of the Through-life Engineering Services Institute, then the Centre for Life-cycle Engineering and Management (CLEM), a world-leading centre of excellence in maintenance and asset management for high value systems, for 11 years. CLEM works in partnership with industry in research and education. He remains as professor of maintenance systems.

Professor Starr read Mechanical Engineering at the University of Leeds, while sponsored by British Aerospace (Civil Aircraft), for which he was awarded first prize in the final year of his apprenticeship. He studied for his doctoral thesis in condition based maintenance for robotic production plant at the University of Manchester, sponsored by Ford and Wolfson Maintenance. He has held academic posts at the University of Huddersfield, the University of Manchester, and the University of Hertfordshire, as Head of the School of Aerospace, Automotive and Design Engineering.

His research work has been funded by EPSRC, the EU, and a wide range of industrial partners. He is a Chartered Engineer, a Fellow of the Institution of Mechanical Engineers, a member of the British Institute of Non-Destructive Testing, a member of the Institute of Asset Management, a member of the International Society for Condition Monitoring, and a member of the Permanent Way Institute. He has published over 150 technical papers from a wide range of collaborative projects with industry, helping to solve real problems and to devise innovative products and services.

Research opportunities

Prof Starr supervises research students focusing on machine and structural damage detection; diagnostics and prognostics; autonomous inspection, detection and robotics; "big data" for system monitoring and control; process monitoring; novel sensing and signal processing; algorithms and artificial intelligence; applications in railway infrastructure and vehicles; aerospace machines especially gearboxes; manufacturing, and defence systems.

Current activities

Projects focus on industrial maintenance research, including autonomous systems, failure modes, vibration and wear debris, wireless sensing, automation, decision-making mathematics, and management processes

2017-2022, EPSRC Platform Grant EP/P019358/1, Through-life performance: From science to instrumentation, £1.18m, Starr et al (PI), with Rolls-Royce, Bombardier Transportation, Network Rail, HVM Catapult.

Autonomous inspection and repair for railway applications:

2023-4, on-going projects in autonomous railway inspection and repair, and digital twins

2020-2022, Network Rail, 22245/02/6559, System Integration (part of In2Smart 2 Grant number 881574 WP13 in Shift2Rail) - unmanned ground vehicle

2020-2021, Network Rail, ECM22352, Autonomous Track Geometry Repair (part of In2Track2 Grant number 826255 in Shift2Rail)

2020-2021, Network Rail, ECM21659, Autonomous ultrasonic testing, (part of In2Track2 Grant number 826255 in Shift2Rail) (PI Durazo)

2020-2021, Network Rail, Remote monitoring of rail defects (part of In2Track2 Grant number 826255 in Shift2Rail), (PI Durazo)

2020-2023, Network Rail, PhDs in location, navigation and scale; modelling and test.

2018, Network Rail, 13453/02/6559 Rail Robot Demonstrator and Cobots, part of Shift2Rail In2Smart WP10, Grant number 730569 CIs Tomiyama, Durazo Cardenas, Kirkwood

2018, Network Rail, 13451/02/6559 Simulations and V&V for Railway Inspection and Repair System (RIRS), part of Shift2Rail In2Smart WP10, Grant number 730569, CI Tomiyama

2018, Network Rail, 11032/02/6559 Non-contact system for detecting rail defects based on laser Doppler vibrometry and thermography, part of Shift2Rail In2Smart WP3, Grant number 730569 CI Durazo Cardenas

2017-2020, Unipart Rail, PhD Studentship in 'Big data' for predictive maintenance

Railway track

2020-2021, SNCF, Whole system design of next generation Switches and Crossings(part of In2Track 2 Grant number 826255 in Shift2Rail)

2018, Network Rail, 3441804 Self-adjusting Switches and Crossings, £49,000, part of Shift2Rail In2Track WP2, Grant number 730841, CI Durazo Cardenas

Gearbox degradation: surface damage and root cracking

2016-2021 IGear: Intelligent Gearbox for Endurance Advanced Rotorcraft - Cleansky 2 738144 - focusing on algorithms for reliable helicopters (coordinator)

Linear actuators - modelling and experimental degradation, diagnostics and prognostics


  • Avio Aerospace
  • BAE Systems PLC
  • Barden Corporation
  • Bombardier Inc
  • Network Rail
  • National Nuclear Laboratory
  • Procter & Gamble
  • QinetiQ Group PLC
  • Rolls-Royce Holdings PLC
  • Schaeffler Technologies AG & Co. KG
  • Schlumberger NV
  • Sellafield Ltd
  • Thales SA
  • UK Space Agency
  • SNCF
  • Unipart Rail


Articles In Journals

Conference Papers