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F

Feng Xia

RMIT University
H指数:69
被引数:1.9万

个人简介

Dr. Feng Xia is a Professor of AI at RMIT University, Melbourne, Australia. He is/was Associate/Guest Editor of over 20 journals (e.g., TIST, TKDD, TOMM, TAI, TNNLS, TCDS, TCSS, TITS, TETC, and TII). He has served as the General Chair, PC Chair, Track Chair, Area Chair, Workshop Chair, or Publicity Chair of over 30 conferences, and (Senior) PC Member of over 100 conferences (e.g., NeurIPS, ICLR, IJCAI, AAAI, WWW/TheWebConf, KDD, and NetSci). Dr. Xia has authored/co-authored over 400 scientific papers in journals and conferences (such as IEEE TAI, TNNLS, TCDS, TETCI, TPAMI, TMC, TVT, TII, TCE, TKDE, TASE, ACM TIST, HEALTH, TOIS, TKDD; NeurIPS, ICLR, IJCAI, AAAI, MM, ICCV, IROS, WWW, ACL, EMNLP, and KDD). He was recognized as a Clarivate Highly Cited Researcher (2019) and a ScholarGPS Highly Ranked Scholar (2024). Dr. Xia received a number of prestigious awards, including e.g. Springer Nature Editor of Distinction Awards 2025 and 2026, IEEE Transactions on Neural Networks and Learning Systems Outstanding Associate Editor of 2023-2024, IEEE Vehicular Technology Society 2020 Best Land Transportation Paper Award, ACM/IEEE JCDL 2020 The Vannevar Bush Best Paper Honorable Mention, and WWW 2017 Best Demo Award. He has delivered numerous keynote speeches and invited talks at international venues worldwide. He is the Chair of IEEE Task Force on Learning for Graphs. His research interests include artificial intelligence, graph learning, brain, robotics, and cyber-physical systems. He is a Fellow of the IEEE.

教育背景

暂无内容

工作经历

暂无内容

荣誉奖项

  1. Clarivate Highly Cited Researcher（2019）｜Clarivate
  2. ScholarGPS Highly Ranked Scholar（2024）｜ScholarGPS
  3. Springer Nature Editor of Distinction Awards（2025）｜Springer Nature
  4. Springer Nature Editor of Distinction Awards（2026）｜Springer Nature
  5. IEEE Transactions on Neural Networks and Learning Systems Outstanding Associate Editor（2023-2024）｜IEEE
  6. The Vannevar Bush Best Paper Honorable Mention（2020）｜ACM/IEEE JCDL
  7. Best Demo Award（2017）｜WWW
  8. Fellow of the IEEE（2026）｜IEEE

研究方向

artificial intelligencegraph learningbrainroboticscyber-physical systems
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王卫 封面图
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