Dr.  Feng Xia Digital Library

Based in Ballart, VIC, Australia
Feng Xia


Dr. Feng Xia is currently an Associate Professor in Institute of Innovation, Science and Sustainability, Federation University Australia. He was a Full Professor and Associate Dean of Research in School of Software, Dalian University of Technology (DUT), China. He is/was on the Editorial Boards of over 10 int’l journals (e.g., ACM Transactions on Knowledge Discovery from Data and IEEE Transactions on Intelligent Transportation Systems). 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) organizer of several conferences. Dr. Xia has authored/co-authored two books, over 300 scientific papers in int’l journals and conferences (such as IEEE TAI, TKDE, TNNLS, TC, TMC, TPDS, TBD, TCSS, TNSE, TETCI, TETC, THMS, TVT, TITS, TASE, ACM TKDD, TIST, TWEB, TOMM, WWW, AAAI, SIGIR, CIKM, JCDL, EMNLP, and INFOCOM) and 3 book chapters. He was recognized as a Highly Cited Researcher (2019) by Clarivate Analytics (Web of Science). Dr. Xia received a number of prestigious awards, including IEEE DSS 2021 Best Paper Award, IEEE Vehicular Technology Society 2020 Best Land Transportation Paper Award, ACM/IEEE JCDL 2020 The Vannevar Bush Best Paper Honorable Mention, IEEE CSDE 2020 Best Paper Award, 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. His research interests include data science, artificial intelligence, graph learning, anomaly detection, and systems engineering. He is a Senior Member of IEEE and ACM, and ACM Distinguished Speaker.

Available Lectures

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  • From Data Science to Graph Learning
    As data (especially big data) become the new oil, data science has recently attracted intensive and growing attention from industry, government, and academia. Data science focuses on deriving...
  • Network Science Meets Data Science: Opportunities and Challenges
    There is an emerging trend of the convergence of network science and data science, though neither of them is new. During the past decade, we have witnessed the exponential growth of data in almost...
  • Scholarly Social Computing
    In an era of big data, it is not surprising that the amount of scholarly data is increasing at an unprecedented speed. Recent years have witnessed the exponential growth of data in all scientific...

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