Prof. Daoyi Dong (IEEE Fellow, ARC Future Fellow)
University of Technology Sydney, Australia

Speech Title: Several results on quantum machine learning

Abstract: In this talk, we will introduce several results on quantum machine learning. Firstly, we will give overview of quantum machine learning. Secondly, we introduce the area of quantum reinforcement learning. Thirdly, we introduce an efficient parameter initialization strategy with theoretical guarantees to enhance the trainability of parameterized quantum circuits. Lastly, we show that noises may make quantum kernel methods to only have poor prediction capability.

Biography: Daoyi Dong (Fellow, IEEE) is currently a Professor and an ARC Future Fellow at the Australian Artificial Intelligence Institute, University of Technology Sydney, Australia and an Honorary Professor at the Australian National University. His research interests include machine learning, quantum estimation and quantum control. Prof. Dong was awarded an ACA Temasek Young Educator Award by The Asian Control Association and is a recipient of a Future Fellowship, an International Collaboration Award and an Australian Post-Doctoral Fellowship from the Australian Research Council, and a Humboldt Research Fellowship from the Alexander von Humboldt Foundation of Germany. He is a Vice President of IEEE Systems, Man and Cybernetics Society, and a member of Board of Governors, IEEE Control Systems Society. He is currently an Associate Editor of Automatica and IEEE Transactions on Cybernetics. He is a Fellow of the IEEE, and a Fellow of the Australian Institute of Physics.