PeopleofSuperintelligence

Researcher

Dagan D. Feng

Also known as David Dagan Feng, (David) Dagan Feng

Dagan D. Feng is a biomedical computing researcher whose work applies machine learning to medical imaging. He studied electrical engineering at Shanghai Jiao Tong University and biocybernetics and computer science at UCLA, then joined the University of Sydney in 1988. At Sydney, he founded the Biomedical & Multimedia Information Technology Group and became a professor at Hong Kong Polytechnic University in 1997; IEEE named him a Fellow in 2003. His work spans multimodal neuroimaging, medical imaging and medical vision-language learning, and he is a Professor Emeritus at the University of Sydney.

Born
1948
Works
963
Citations
25,550
h-index
76
Badges

Years link to their sources. Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 1982–1988

    Engineering and computing degrees

    He earns an MEng in electrical engineering and computing science at Shanghai Jiao Tong University in 1982, an MSc in biocybernetics at UCLA in 1985, and a PhD in computer science at UCLA in 1988.

  2. 1988

    Riverside to Sydney

    After a brief assistant professorship at the University of California, Riverside, he joins the University of Sydney at the end of 1988 as a lecturer, then becomes a senior lecturer and reader.

  3. 1997

    A PolyU professorship

    Hong Kong Polytechnic University appoints him professor in 1997.

  4. 2003

    An IEEE Fellowship

    IEEE names him a Fellow in 2003 for contributions to modeling and data processing for biomedical and multimedia applications.

  5. 2015–2016

    Neuroimaging workflows and disease patterns

    In 2015, he coauthors a review of multimodal neuroimaging workflows and the computing platforms they use. In 2016, he and Royal Prince Alfred Hospital researchers receive an Australian Research Council Linkage grant to develop methods that extract disease patterns from medical images with deep learning and image processing.

  6. By 2021

    BMIT and the IMECS committee

    In 2021, he serves as honorary co-chair of the IMECS program committee and as director of Sydney's Biomedical & Multimedia Information Technology Research Group, which he founded.

  7. 2024–2025

    Medical vision-language learning

    In 2024, he coauthors “Enhancing medical vision-language contrastive learning via inter-matching relation modelling,” which uses medical reports as weak supervision for image-text alignment and proposes a relation-enhanced contrastive framework. The team evaluates the framework on segmentation, zero-shot classification, linear classification and cross-modal retrieval; IEEE Transactions on Medical Imaging publishes the paper in 2025.

  8. Since 2021

    Professor Emeritus at Sydney

    He becomes a Professor Emeritus at the University of Sydney in 2021 and holds the title.

Career

  1. Since 1988University of SydneyLecturer, Founder
  2. 2013–2017Australian National University
  3. 2013–2017CSIRO
  4. 2008–2025Shanghai Jiao Tong University
  5. 1997–2016Hong Kong Polytechnic UniversityProfessor
  6. Until 1988University of California, RiversideAssistant Professor

Education

  1. 1988University of California, Los AngelesPhD
  2. 1985University of California, Los AngelesMSc
  3. 1982Shanghai Jiao Tong UniversityMEng

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

  1. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Sydney. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Sydney. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. 5 of the 25 people with the most-cited recent papers also lead on career citationsIncludes University of Sydney. We compare citations to 2023–2025 papers with career citations and h-index, after correcting reviewed publication-date errors: who leads, when they started and where they work.
  4. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University of Sydney. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Dagan D. Feng yet. Send us a free-licensed photo.

  1. Prof. David Dagan Feng homepage eie.polyu.edu.hk. Checked 21 October 2026.
  2. IEEE New South Wales ewh.ieee.org. Checked 21 October 2026.
  3. Multimodal neuroimaging computing: the workflows, methods, and platforms pmc.ncbi.nlm.nih.gov. Checked 21 October 2026.
  4. Research funding for industry-linked projects sydney.edu.au. Checked 21 October 2026.
  5. The IMECS 2021 Program Committee iaeng.org. Checked 21 October 2026.
  6. Enhancing medical vision-language contrastive learning via inter-matching relation modelling arxiv.org. Checked 21 October 2026.
  7. Publications - Mingyuan Meng / Homepage mungomeng.github.io. Checked 21 October 2026.
  8. Notable university members - The University of Sydney sydney.edu.au. Checked 21 October 2026.