Academic Staff

Engineering Asset Management Group | Academic Staff

Richard Dwight

Developed and now directs the engineering asset management and rolling stock engineering programs at the University of Wollongong within which he has taught widely.Leads major research programs in engineering asset management and railway wheel-rail noise, publishing over 50 papers in these specific areas. He has produced numerous reports for industry related to asset management systems with particular focus on asset replacement and maintenance requirements analysis processes. He also teaches into the engineering program, particularly in mechanics of solids and mechanical design. Richard spent 19 years in industry including roles as investigation engineer and engineering manager. He directs the research group in engineering asset management at the University of Wollongong. He is supervising PhD students doing research projects in the fields of systems engineering and asset management.

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Tieling Zhang

Received a PhD degree in engineering. He has very strong expertise in data processing and modelling, system reliability engineering, condition based prediction, process simulation and optimisation. He has published 70 research articles in the related fields and completed more than 12 major research projects. He is an invited referee serving for over 20 international journals and, reviewer/technical team member for many international conferences. He holds 5 patents with 7 others published and pending for grant. He has been teaching undergraduate and postgraduate subjects under the program of engineering asset management. He is working on EPCRC projects by taking the leadership and supervising PhD students who are doing projects in the fields of systems engineering and engineering asset management.

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Khaled El-Akruti

Obtained his PhD in engineering asset management from University of Wollongong. Currently, he is working on EPCRC projects and involved in supervision of PhD and postgraduate students. He is teaching undergraduate and postgraduate subjects covered under the program of engineering asset management. He has published over 16 articles, numerous research reports for production industry and he has over 12 years’ experience in teaching in universities. He has over 13 years of experience in steel industry and has worked on a number of projects in relation to asset replacement and operation optimisation.

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Neaz Sheikh

Senior Lecturer at University of Wollongong, is a structural engineer with expertise in structural dynamics, earthquake engineering, protective technology and structural reliability. In the past 10 years, he has been researching and consulting widely in these fields and has published more than 60 technical articles including 25 journal articles. Dr. Sheikh supervised to graduation 3 PhD students. He is currently supervising 10 PhD students. Dr. Sheikh frequently reviews articles for the leading structural engineering journals and is on the editorial review board of the International Journal of Geotechnical Earthquake Engineering.

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Abheek Basu

Design and stress analysis engineer with over 12 years of experience working for/or consulting to heavy industry including the mining, steel, cement, and aluminium processing sectors. With a PhD in Mechanical Engineering focusing on the computational stress analysis of damaged boiler tubing, he has high level skills in numerical methods, scientific programming and failure analysis including creep and fatigue life assessment. Abheek is currently teaching undergraduate and postgraduate subjects in engineering design at the University of Wollongong. Wenxu Li Working in University of Wollongong as a postdoctoral research fellow. He received his PhD degree in engineering from University of OWollongong in 2014. He is now working on EPCRC research projects with research focus on pipeline deterioration modelling using neural networks and stochastic modelling approaches. His research interests include railway noise modelling and prediction, dynamic system simulation, fault diagnostics and condition prediction.

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Last reviewed: 3 September, 2018