Assoc Prof Feng Xia

PositionAssociate Professor, Data Science  
Office T251 (Mt Helen)
Phone +61 3 5327 6245


  • PhD, Zhejiang University
  • BEng, Zhejiang University


Dr. Feng Xia is currently an Associate Professor of Data Science in Institute of Innovation, Science and Sustainability, Federation University Australia. Before joining Federation University, he has been a Full Professor and former Associate Dean of Research in School of Software, Dalian University of Technology (DUT), China.

Dr. Xia has authored/co-authored two books, over 300 scientific papers in int’l journals and conferences (such as IEEE TKDE, TC, TMC, TPDS, TBD, TCSS, TETC, THMS, TETCI, TVT, TII, TITS, TASE, IEEE/ACM TON, ACM TKDD, TIST, TWEB, TOMM, WWW, AAAI, SIGIR, CIKM, JCDL, EMNLP, and INFOCOM) and 3 book chapters. He is/was on the Editorial Boards of over 10 int’l journals. He has served as the General Chair, Program Committee Chair, Workshop Chair, or Publicity Chair of over 30 int’l conferences and workshops, and Program Committee Member of over 90 conferences. He is also the Guest Editor of over 10 journal special issues and a (founding) organiser of several conferences.

Dr. Xia is recognised as a Highly Cited Researcher (2019) by Clarivate Analytics (Web of Science). His name has been included on Elsevier’s Most Cited Chinese Researchers for six consecutive years (2014-2019; ever since its inaugural version). Dr. Xia received a number of prestigious awards, including IEEE Vehicular Technology Society 2020 Best Land Transportation Paper Award, ACM/IEEE JCDL 2020 The Vannevar Bush Best Paper Honorable Mention, WWW 2017 Best Demo Award, IEEE DataCom 2017 Best Paper Award, IEEE UIC 2013 Best Paper Award, and IEEE Access Outstanding Associate Editor. He has been invited as Keynote Speaker at seven international conferences, and delivered a number of Invited Talks at international conferences and many universities worldwide. He is a Senior Member of IEEE and ACM.

Research interests

  • Data Science
  • Artificial Intelligence
  • Social Computing