Dacheng Tao

Award Recipient
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Dacheng Tao received his BEng from the University of Science and Technology of China (USTC), his MPhil from the Chinese University of Hong Kong, and his PhD from the University of London. He is currently the director of the JD Explore Academy and a vice president in JD.com, an advisor and chief scientist of the digital science institute in the University of Sydney (USYD), distinguished visiting professor in Tsinghua University, and grand master adjunct professor in USTC.

Previously, he was a Professor and ARC Laureate Fellow in USYD, Professor and ARC Future Fellow in the University of Technology Sydney, a Nanyang Assistant Professor in the Nanyang Technological University, an Assistant Professor in the Hong Kong Polytechnic University.

His research interests spread across subareas in artificial intelligence (AI), including computer vision, data mining, deep learning, image processing, and machine learning. His research results have expounded in 400+ publications at prestigious journals and conferences, with several best paper awards, such as the IEEE ICDM’07 best theory/algorithm paper runner up award, the IEEE ICDM’13 best student paper award, the 2014 ICDM 10-year highest-impact paper award, the IJCAI 2017 distinguished student paper award, the IJCAI 2018 distinguished paper award, and the 2017 IEEE signal processing society best paper award.

He has been ranked as a Highly-Cited Researcher in Engineering since 2014 and Computer Science since 2015. His publications have been cited 58K+ times, and his H-Index is 126. He received the 2015 Australian Museum Scopus-Eureka Prize, the 2015 ACS Gold Disruptor Award, the 2015 UTS Vice-Chancellor’s Medal for Exceptional Research, the 2018 IEEE ICDM Research Contributions Award, the 2020 USYD Vice-Chancellor’s Award for Outstanding Research, and the 2020 Australian Museum Eureka Prize for Excellence in Data Science. He is a Fellow of the IEEE, OSA, IAPR, AAAS, ACM, and the Australian Academy of Science.



Awards

2021 Edward J. McCluskey Technical Achievement Award
“For exceptional contributions to representation learning and its applications”
Learn more about the Edward J. McCluskey Technical Achievement Award