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Raymond Chiong
Affiliation
University of Newcastle, Callaghan, NSW, Australia
Topic
Evolutionary Algorithms,Actual Production,Energy Consumption,Makespan,Neural Network,Objective Value,Processing Time,Recurrent Neural Network,Tabu Search,Tabu Search Algorithm,Total Energy Consumption,Acceleration Scheme,Actual Point,Actual Production Process,Advantage Of The Ability,Ambiguous Language,Ant Colony Optimization,Applicability Domain,Average Precision,Balanced Accuracy,Batch Mode,Batch Processing Machine,Binary String,Candidate Solutions,Casting Process,Charging Time,Combination Of Functions,Complete Schedule,Completion Time,Comprehensive Experimental Results,Computer Vision,Conditional Value At Risk,Continuous Casting,Continuous Casting Process,Convolutional Layers,Convolutional Neural Network,Convolutional Neural Network Architecture,Cost Function,Cost Value,Covariate Information,Crossover Operator,Current Population,Data Pre-processing,Decimal Value,Deck Of Cards,Deep Convolutional Neural Network,Deep Neural Network,Dense Layer,Direct Benefits,Distributionally Robust,
Biography
Raymond Chiong received the Ph.D. degree in computer science from the University of Melbourne, Parkville, VIC, Australia, in 2012.
He is currently an Associate Professor with the School of Information and Physical Sciences, University of Newcastle, Callaghan, NSW, Australia. He has been actively pursuing research related to the use of automated intelligent computing methods, including machine learning and optimisation algorithms, with applications in energy load forecasting, energy-efficient production scheduling, computer vision, and image processing. To date, he has produced/coauthored more than 200 refereed publications and attracted over 3 million dollars in research and industry funding. He is the Editor-in-Chief for the Journal of Systems and Information Technology, and an Editor for Engineering Applications of Artificial Intelligence.
He is currently an Associate Professor with the School of Information and Physical Sciences, University of Newcastle, Callaghan, NSW, Australia. He has been actively pursuing research related to the use of automated intelligent computing methods, including machine learning and optimisation algorithms, with applications in energy load forecasting, energy-efficient production scheduling, computer vision, and image processing. To date, he has produced/coauthored more than 200 refereed publications and attracted over 3 million dollars in research and industry funding. He is the Editor-in-Chief for the Journal of Systems and Information Technology, and an Editor for Engineering Applications of Artificial Intelligence.