Jianfei Cai

Professor

Accepting PhD Students

PhD projects

Vision and language, 3D vision

19982021

Research activity per year

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Personal profile

Biography

Jianfei is a Professor at Faculty of IT, Monash University, where he currently serves as the Head for the Data Science & AI Department. Before that, he was a full professor, a cluster deputy director of Data Science & AI Research center (DSAIR), Head of Visual and Interactive Computing Division and Head of Computer Communications Division in Nanyang Technological University (NTU). His major research interests include computer vision, multimedia and visual computing. He has published more than 200 technical papers in international conferences and journals. He is a co-recipient of paper awards in ACCV, ICCM, IEEE ICIP and MMSP. He has served as an Associate Editor for IEEE T-IP, T-MM, T-CSVT and Visual Computer as well as serving as Area Chair for ICCV, ECCV, ACM Multimedia, ICME and ICIP. He was the Chair of IEEE CAS VSPC-TC during 2016-2018. He had also served as the leading TPC Chair for IEEE ICME 2012 and the best paper award committee chair/co-chair for IEEE T-MM 2020/2019. He is a Fellow of IEEE.

(Ad: Positions might be available for top PhD students and visiting students in computer vision and deep learning areas.)

(Personal webpage: https://jianfei-cai.github.io/)

(Google Scholar: https://scholar.google.com/citations?hl=en&user=N6czCoUAAAAJ)

(Office address: Room 201-B20 Exhibition WalkClayton VIC 3800)

(For DSAI Department matters, please send email to fit-dsai@monash.edu)

Education/Academic qualification

Electrical Engineering, Doctor of Philosophy, University of Missouri Columbia

Award Date: 19 May 2002

Electrical Engineering, Master of Engineering, Southeast University

Award Date: 24 Apr 1997

Electrical Engineering, Bachelor of Engineering, Nanjing University of Aeronautics and Astronautics

Award Date: 24 Jun 1994

Research area keywords

  • visual computing
  • computer vision
  • vision and language
  • 3D imaging and analysis
  • deep learning
  • Multimedia

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