Key dates and participating speakers

Tuesday 18 to Thursday 20 June 2024
Milton Hill House, Oxford, UK 



Key dates
Submission of proposals for structured sessions5 January 2024
Deadline for structured session abstract submission2 February 2024
Deadline for general abstract submission (not more than 200 words)
Still accepting
(subject to availability)
Notification of abstract acceptance (not later than)
29 March 2024
Deadline for submission of full-length papers (to ensure publication of your paper you must adhere to this
date; any papers submitted after this date will not be included)

12 April 2024
Notification of full-length paper acceptance (not later than) 26 April 2024
Early registration 17 May 2024
Speaker registration 17 May 2024



 
  Plenary speakers

SpeakersTitle
Dr J Griffaton To be confirmed 
Dr M KhanTo be confirmed
Professor W Mansoor To be confirmed 
Professor Z Peng To be confirmed 



 
  Distinguished Overview Speakers

SpeakersTitle
Professor R Burdzik Quantum physics and artificial intelligence: current challenges and opportunities in technical diagnostics and condition monitoring 
Professor H R KarimiDeep information fusion for mechanical fault diagnosis
Professor J Lacaille To be confirmed 
Professor N Vyas To be confirmed 



 
  Structured session organisers

SpeakersTitle
Dr L Alboul Digital health monitoring 
Dr S Ganeriwala To be confirmed 
Professor L GelmanCondition monitoring for renewable energy assets
Professor A Hope Vibration monitoring and analysis
Dr E Juuso Advanced signal processing and diagnostics in condition monitoring
D Manning-OhrenCondition monitoring compromises
S Mills Condition monitoring management, training and certification
Professor S NorooziHuman dynamics and other health related monitoring
Professor F Pellicano and
Dr A Zippo
Innovations in signal processing and modelling for complex industrial systems 
Professor Z K Peng and
Professor D Wang
Advances in interpretable condition monitoring and diagnostic methods 
Dr A Rahbarimanesh Data-driven and physics-based modelling for condition monitoring of industrial assets 
Professor M Shafiee Computer vision and deep learning for structural health monitoring of wind turbines 
D Whittle Visualising vibration a 'game changer' for troubleshooting, diagnostics and root cause analysis



 
For further information contact: Events and Awards Department, The British Institute of Non-Destructive Testing,
Midsummer House, Riverside Way, Bedford Road, Northampton NN1 5NX, UK.
Tel: +44 (0)1604 438300; Email: cm_mfpt@bindt.org; Web: www.cm-mfpt.org