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- Computing and Processing
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- General Topics for Engineers
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Eryk Dutkiewicz
Also published under:E. Dutkiewicz
Affiliation
Faculty of Engineering and IT, University of Technology Sydney, Sydney, NSW, Australia
Topic
Deep Neural Network,Objective Function,Convex Optimization Problem,Optimization Problem,Deep Reinforcement Learning,Feasible Point,Antenna Array,Bisection,Federated Learning,Reconfigurable Intelligent Surface,Resource Allocation,Sum-rate Maximization,Average Reward,Base Station,Internet Of Things,Optimal Policy,Power Constraint,Satellite Networks,Achievable Rate,Bottom Of Page,Computational Complexity,Computationally Intractable,Deep Learning,Edge Server,Global Model,Learning Algorithms,Learning Process,Low Earth Orbit,Sum Rate,Time Slot,Wireless Networks,Cloud Computing,Cognitive Networks,Computational Resources,Demand For Resources,Dual Network,Fast Fourier Transform,Internet Of Things Devices,Intrusion Detection,Intrusion Detection System,Mobile Users,Multiple-input Multiple-output,Neural Network,Number Of Chains,Power Consumption,Proximal Policy Optimization,Reward Function,State Space,Support Vector Machine,Types Of Attacks,
Biography
Eryk Dutkiewicz (Senior Member, IEEE) received the B.E. degree in electrical and electronic engineering and the M.Sc. degree in applied mathematics from The University of Adelaide, in 1988 and 1992, respectively, and the Ph.D. degree in telecommunications from the University of Wollongong, in 1996. His industry experience includes management of the Wireless Research Laboratory at Motorola, in 2000. He is currently the Head of the School of Electrical and Data Engineering, University of Technology Sydney, Australia. He holds a Professorial Appointment with Hokkaido University, Japan. His current research interests include 5G/6G and the Internet-of-Things networks.