Junjie Zhang

Associate Professor

Calculated based on number of publications stored in Pure and citations from Scopus
20162024

Research activity per year

Personal profile

Personal profile

Dr. Junjie Zhang is currently an Associate Professor at the Department of Intelligent Science, School of Advanced Technology, Xi’an Jiaotong-Liverpool University (XJTLU). He earned his Ph.D. in Information Technology from the University of Technology Sydney in 2019 and completed his Bachelor's degree in Computer Science and Technology at Nanjing University of Science and Technology in 2010.

Before joining XJTLU, he held a postdoctoral position at the Australian Institute for Machine Learning, The University of Adelaide, from December 2018 to November 2020. He also served as a Lecturer at the School of Communication and Information Engineering, Shanghai University, where he was elected to the Shanghai Oversea Talent Program, from 2021 to 2024.

His research interests include computer vision, machine learning, and multimedia data analysis, with a focus on multi-modal learning, remote sensing interpretation, and intelligent object perception. Dr. Zhang has published over 40 papers, including top-tier journals and conferences IEEE Trans, CVPR, ICCV, ECCV, AAAI, IJCAI, ICME, ICASSP. His research has been supported by both government and industry, including the NSFC Young Program and State Grid.

Research interests

Computer vision, Machine learning, Multimedia Data Analysis

Multi-modal Learning, Remote Sensing Interpretation, Intelligent Object Perception

Experience

Associate Professor, Department of Intelligent Science, SAT, XJTLU, 2024- Now

Lecturer, School of Communication and Information Engineering, Shanghai University, 2021-2024

Postdoc, Australian Institute for Machine Learning, The University of Adelaide, 2018-2020

Teaching

INT402 Data Mining and Big Data Analytics

Related documents

Education/Academic qualification

PhD, University of Technology Sydney

Award Date: 20 Aug 2019

Bachelor, Nanjing University of Science and Technology

Award Date: 15 Jun 2014

Person Types

  • Staff

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