# Dacheng Tao > computer science researcher, University of Sydney **Wikidata**: [Q29259267](https://www.wikidata.org/wiki/Q29259267) **Wikipedia**: [English](https://en.wikipedia.org/wiki/Dacheng_Tao) **Source**: https://4ort.xyz/entity/dacheng-tao ## Summary Dacheng Tao is a prominent computer scientist and researcher currently serving as academic staff at the University of Sydney. He is widely recognized for his significant contributions to representation learning and its applications, earning him fellowships in prestigious organizations including the ACM, IEEE, and the Australian Academy of Science. ## Biography - **Born:** 2000 (per source material) - **Education:** University of Science and Technology of China; The Chinese University of Hong Kong; University of London - **Known for:** Primary contributions to representation learning and its applications - **Employer(s):** University of Sydney; University of Technology Sydney; Nanyang Technological University; Hong Kong Polytechnic University - **Field(s):** Computer Science ## Contributions Dacheng Tao has made extensive contributions to the field of computer science, with a specialized focus on representation learning. His research in this area was specifically cited by the Association for Computing Machinery (ACM) when he was named an ACM Fellow in 2019. Tao has held various academic and research positions across international institutions, including Nanyang Technological University in Singapore and the Hong Kong Polytechnic University, before his roles at the University of Technology Sydney and the University of Sydney. Beyond his individual research, Tao has been a prolific doctoral advisor, guiding the development of several researchers in the field. His former doctoral students include Wei Bian, Tongliang Liu, Meng Fang, Changxing Ding, and Tao Liu. His work is highly integrated into the global scientific community, as evidenced by his membership in the Global Young Academy (2015–2020) and his election to the Informatics section of Academia Europaea in 2016. His research impact is tracked through major academic identifiers including a Google Scholar h-index and significant contributions recorded on platforms like dblp and Scopus. ## FAQs ### Q: What is Dacheng Tao's most significant professional recognition? A: Dacheng Tao has received several top-tier honors, most notably being named an ACM Fellow in 2019 for his work in representation learning and being elected as a Fellow of the Australian Academy of Science in 2018. ### Q: Which universities has Dacheng Tao been affiliated with? A: He has held positions or received degrees from the University of Sydney, University of Technology Sydney, Nanyang Technological University, Hong Kong Polytechnic University, University of London, The Chinese University of Hong Kong, and the University of Science and Technology of China. ### Q: Who were Dacheng Tao's doctoral advisors? A: His doctoral research was advised by computer scientists Stephen J. Maybank and David Gavin Messerschmitt. ## Why They Matter Dacheng Tao is a central figure in the advancement of representation learning, a critical subfield of computer science that enables machines to interpret and organize complex data. His influence is marked by his "Laureate" status in the Australian research community, having been awarded the Australian Laureate Fellowship in 2017. This award, combined with his fellowships in the AAAS, IEEE, and ACM, places him among the most decorated computer scientists currently active in Australia. His work has not only advanced theoretical understanding but has also built a legacy through the mentorship of numerous PhD students who now contribute to the global research infrastructure. ## Notable For * **ACM Fellow (2019):** Recognized for contributions to representation learning and its applications. * **Australian Laureate Fellowship (2017):** Awarded by the Australian Research Council. * **Fellow of the Australian Academy of Science (2018):** Elected for outstanding contributions to science. * **Academia Europaea Member:** Elected to the Informatics section in 2016. * **AAAS Fellow (2017):** Fellow of the American Association for the Advancement of Science. ## Body ### Academic Background Dacheng Tao's academic foundation was established through studies at the University of Science and Technology of China, followed by advanced education at The Chinese University of Hong Kong and the University of London. During his doctoral training, he was advised by Stephen J. Maybank and David Gavin Messerschmitt. ### Career and Institutional Affiliations Tao has maintained a distinguished career across several leading research institutions: * **University of Sydney:** Current/recent affiliation as a computer science researcher. * **University of Technology Sydney:** Former employer and site of several doctoral supervisions. * **Nanyang Technological University:** Served as an employer (records indicate employment updated in 2019). * **Hong Kong Polytechnic University:** Served as an employer (records indicate employment updated in 2019). ### Professional Fellowships and Memberships Tao is a member of several elite scientific societies: * **Association for Computing Machinery (ACM):** Named Fellow on December 11, 2019. * **IEEE:** Holds the rank of IEEE Fellow. * **Academia Europaea:** Member of the Informatics section since 2016 (Member ID: Tao_Dacheng). * **Global Young Academy:** Member from 2015 to 2020. ### Research Supervision Tao has mentored a significant number of doctoral students who have successfully completed their Ph.D. programs, including: * **Meng Fang:** Ph.D. from University of Technology, Sydney (2015). * **Changxing Ding:** Ph.D. from University of Technology, Sydney (2016). * **Tao Liu:** Ph.D. from University of California, Merced (2013). * **Tongliang Liu:** Currently a researcher at the University of Sydney. ## Schema Markup ```json { "@context": "https://schema.org", "@type": "Person", "name": "Dacheng Tao", "jobTitle": "Computer science researcher", "worksFor": [ { "@type": "Organization", "name": "University of Sydney" }, { "@type": "Organization", "name": "University of Technology Sydney" }, { "@type": "Organization", "name": "Nanyang Technological University" }, { "@type": "Organization", "name": "Hong Kong Polytechnic University" } ], "birthDate": "2000", "gender": "male", "alumniOf": [ { "@type": "EducationalOrganization", "name": "University of Science and Technology of China" }, { "@type": "EducationalOrganization", "name": "The Chinese University of Hong Kong" }, { "@type": "EducationalOrganization", "name": "University of London" } ], "knowsAbout": [ "Computer Science", "Representation Learning" ], "sameAs": [ "https://www.sydney.edu.au/engineering/about/our-people/academic-staff/dacheng-tao.html", "https://www.uts.edu.au/staff/dacheng.tao" ], "description": "Dacheng Tao is a computer science researcher at the University of Sydney, recognized as an ACM and IEEE Fellow for his work in representation learning." } ## References 1. [Source](https://www.sydney.edu.au/engineering/about/our-people/academic-staff/dacheng-tao.html) 2. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7225-5449/employment/1494738) 3. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7225-5449/employment/1494752) 4. [Source](https://ieeexplore.ieee.org/ielx7/6745853/7081731/07091110.pdf) 5. [Source](https://www.science.org.au/fellowship/fellows/new-fellows/fellows-elected-2018) 6. [Source](https://www.science.org.au/profile/dacheng-tao) 7. [Source](https://www.aaas.org/news/2017-aaas-fellows-recognized-advancing-science) 8. [Source](https://www.acm.org/media-center/2019/december/fellows-2019) 9. [Source](https://web.archive.org/web/20220929051214/https://www.arc.gov.au/funding-research/funding-schemes/discovery-program/australian-laureate-fellowships/2017-laureate-profile-professor-dacheng-tao) 10. [Source](https://www.ae-info.org/ae/User/Tao_Dacheng)