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个人简介
Dr Alireza Daneshkhah is currently an Associate Professor and Curriculum Lead Data Science and AI at Faculty of Engineering, Environment and Computing, and Centre for Computational Science and Mathematical Modelling of Coventry University. Prior to this position, he was a research Fellow in the Warwick Centre for Predictive Modelling (WCPM). Before joining WCPM, he was a Lecturer and director of Utility Asset Management course. He holds a PhD (Warwick), is a fellow of the Royal Statistical Society and a member of International Society of Bayesian Analysis. He is a Lecturer and director of Cranfield’s Utility Asset Management course. His current research interests are in predictive based maintenance; optimal maintenance; Proactive asset management; identifying the dominant factors affecting the performance and reliability of networked infrastructure; probabilistic risk analysis of climate change impact on water systems; managing uncertainty in Condition Assessment of Water Systems; reliability analysis of the assets under natural hazard threats; uncertainty quantification of and sensitivity analysis of complex engineering and environmental systems; expert judgment techniques to assess asset condition; modelling multivariate data and uncertain quantities using advanced graphical models including Bayesian networks. His other research interests are sensitivity and uncertainty analysis of complex system availability & reliability using the computationally fast emulators. Alireza is co-author of two books on expert judgment and advanced reliability methods and has an established list of published journal papers, book chapters and conference communications to his name.
研究兴趣
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Computers in Biology and Medicineno. C (2024): 108382-108382
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2024): 107536
Research Square (Research Square) (2023)
The Science of the total environment (2023): 168814-168814
4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering (2023)
COMMUNICATIONS IN STATISTICS-THEORY AND METHODSno. 11 (2023): 3581-3597
MACHINE LEARNING AND KNOWLEDGE EXTRACTIONno. 4 (2023): 1493-1518
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