Dacheng Tao

From Wikipedia, the free encyclopedia

Dacheng Tao FAA is an Australian engineer and academic. He is currently a professor of computer science at the University of Sydney, Australia. He received a PhD in 2007 from the University of London under Stephen Maybank, with a thesis titled Discriminative linear and multilinear subspace methods.[1] He was named a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2015[2] for his contributions to pattern recognition and visual analytics. He was awarded an Australian Laureate Fellowship in 2017.[3] In 2018, Tao was also elected a Fellow of the Australian Academy of Science (FAA) for his "ground-breaking contributions in artificial intelligence, computer vision image processing and machine learning.[4] He was elected as an ACM Fellow in 2019 "for contributions to representation learning and its applications".[5] He was selected to the Global Young Academy.[6] Tao won the Australian Museum's Eureka Prize for Excellence in Data Science in 2020.[7] He has written over 1200 publications across various Artificial Intelligence fields, including pattern recognition, visual analytics, and statistical learning theory.[8]

References[edit]

  1. ^ "Dacheng Tao". Mathematics Genealogy Project. Retrieved 17 December 2022.
  2. ^ "2015 elevated fellow" (PDF). IEEE Fellows Directory.
  3. ^ "Fellowships and training centres accelerate research capacity". University of Sydney. 5 June 2017. Retrieved 21 January 2018.
  4. ^ "Professor Dacheng Tao". www.science.org.au. Retrieved 16 June 2018.
  5. ^ 2019 ACM Fellows Recognized for Far-Reaching Accomplishments that Define the Digital Age, Association for Computing Machinery, retrieved 11 December 2019
  6. ^ "Dacheng Tao". Retrieved 5 September 2021.
  7. ^ "2020 Australian Museum Eureka Prize winners". The Australian Museum. Archived from the original on 24 November 2020. Retrieved 9 December 2020.
  8. ^ "Most prolific dblp authors". dblp.uni-trier.de. Retrieved 24 September 2021.