PeopleofSuperintelligence

Researcher

Guangquan Zhang

Also known as Guang Zhang, Guang-Quan Zhang

Guangquan Zhang is a mathematician and machine learning researcher at the University of Technology Sydney whose work spans fuzzy machine learning, transfer learning and concept drift, the study of streaming data whose distribution changes over time. After serving as a full professor of mathematics at Hebei University in China from 1993 to 1997, he earned a PhD in applied mathematics from Curtin University of Technology in 2001 and received an ARC QEII Fellowship in 2005. With Jie Lu and colleagues, he coauthored the 2007 book Multi-Objective Group Decision Making and a 2018 review of learning under concept drift in IEEE Transactions on Knowledge and Data Engineering. A 2020 paper he wrote with Lu and Hua Zuo, Fuzzy Multiple-Source Transfer Learning, won the IEEE Transactions on Fuzzy Systems Outstanding Paper Award at Fuzz-IEEE 2023. He is an adjunct fellow at UTS's Australian Artificial Intelligence Institute and co-directs its Decision Systems and e-Service Intelligence Lab.

Timeline

  1. 1993–1997

    Mathematics professor at Hebei

    From 1993 to 1997, he is a full professor in the Department of Mathematics at Hebei University in China.

  2. 2001

    A PhD at Curtin

    He receives a PhD in applied mathematics from Curtin University of Technology in Australia in 2001.

  3. 2005

    An ARC QEII Fellowship

    In 2005, he receives an Australian Research Council (ARC) QEII Fellowship.

  4. 2007

    Multi-objective group decision making

    With UTS colleagues Jie Lu and Fengjie Wu and Da Ruan of the Belgian Nuclear Research Centre, he publishes Multi-Objective Group Decision Making with Imperial College Press in 2007. The book sets out fuzzy models for multi-objective, multi-criteria and group decision problems and provides two decision support software systems for applying its methods.

  5. 2018–2020

    A review of concept drift

    He coauthors "Learning under Concept Drift: A Review" with Jie Lu, João Gama and three other researchers, published in IEEE Transactions on Knowledge and Data Engineering in 2018 and posted to arXiv in April 2020. The review covers over 130 publications on changes in streaming data over time and organizes the field around drift detection, understanding and adaptation.

  6. 2020–2023

    Fuzzy transfer learning awards

    With Jie Lu and Hua Zuo, he publishes "Fuzzy Multiple-Source Transfer Learning" in IEEE Transactions on Fuzzy Systems in 2020, and the paper wins the journal's Outstanding Paper Award at Fuzz-IEEE 2023, held in Korea in August 2023. At the same conference, a paper he coauthors with Keqiuyin Li, Jie Lu and Hua Zuo wins the FUZZ-IEEE Best Paper Award as the first work to bring fuzzy systems into a deep transfer model for universal source-free domain adaptation.

  7. As of October 2026

    Adjunct fellow at AAII

    As of October 2026, he is an adjunct fellow at UTS's Australian Artificial Intelligence Institute and co-directs its Decision Systems and e-Service Intelligence Lab with Yi Zhang, a group working on transfer learning, concept drift, reinforcement learning and recommender systems. His research covers fuzzy measure, fuzzy optimization and fuzzy machine learning, and he has won 10 ARC Discovery Project grants.

  1. Google had the most people shaping AI every year from 2014 to 2025Our estimates of which organizations employed the most people shaping AI from 1961 to 2025, with a year-by-year chart.
  2. The United States employs an estimated 53% of people in our data with a known employment countryOur estimates of where AI careers are concentrated now and how countries’ shares of dated positions changed over time.
  3. 46% of living people in our data with known birth and employment countries work outside their birth countryOur estimate of cross-border careers in AI, from country of birth and the country of each current organization.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionOur estimates of where the people shaping AI studied and where their careers led, from education records in cited biographies.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. Guangquan Zhang | About | University of Technology Sydney profiles.uts.edu.au. Checked 19 October 2026.
  2. [2008.03662] Concept Drift Detection: Dealing with Missing Values via Fuzzy Distance Estimations ar5iv.labs.arxiv.org. Checked 19 October 2026.
  3. Multi-Objective Group Decision Making:Methods, Software and Applications with Fuzzy Set Techniques(With CD-ROM) ideas.repec.org. Checked 19 October 2026.
  4. Multi-objective group decision making: Methods, software and applications with fuzzy set techniques researchportal.sckcen.be. Checked 19 October 2026.
  5. [2004.05785] Learning under Concept Drift: A Review arxiv.org. Checked 19 October 2026.
  6. AAII wins three Fuzz-IEEE Outstanding Paper Awards 2023 uts.edu.au. Checked 19 October 2026.
  7. Decision Systems and e-Service Intelligence Lab | University of Technology Sydney uts.edu.au. Checked 19 October 2026.