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Jun Cheng received the B. E. degree in electronic engineering and information science from the University of Science and Technology of China,
and the Ph. D. degree from Nanyang Technological University, Singapore. He is now a principal scientist in the Institute for Infocomm
Research, A*STAR, working on AI for medical imaging, robust vision & perception, and machine learning. He has authored/co-authored over 200 publications at prestigious
journals/conferences, such as TMI, TIP, TBME, IOVS, JAMIA, MICCAI, CVPR and invented more than 20 patents. He has received the IES Prestigious Engineering Achievement Award 2013.
He serves as reviewers for many journal/conferences and area chairs for MICCAI, AAAI, ICLR, NeurIPS. He is currently associate editor for IEEE TIP and IEEE TMI.
Research Interest:
Computer Vision: 3D Vision, Robust Vision and Perception
Medical Image Computing: Medical Image Registration, Medical Imaging, Medical Image Segmentation
Machine Learning: Unserpervised Learning, Multimodal Data Learning, Learning With Less Data, Physical-driven Deep Learning
Chinese Government Scholarship: Chinese CSC Scholarships
support exchange PhD students from China.
A*STAR SIPGA: A*STAR SIPGA The Singapore International Pre-Graduate Award (SIPGA) supports short-term
research attachments for top international Undergraduate & Master students at A*STAR.
A*STAR SINGA: A*STAR SINGA Scholarship supports international students who wish to pursue their PhDs from Singapore Universities (NUS, NTU, and SUTD).
2023-03: One paper "Perceptual Quality Assessment of Enhanced Colonoscopy Images: A Benchmark Dataset and An Objective Method" has been accepted by TCSVT.
2023-01: One paper "CLC-Net: Contextual and Local Collaborative Network for Lesion Segmentation in Diabetic Retinopathy Images" has been accepted by Neurocomputing.
2022-12: One paper "CPP-Net: Context-aware Polygon Proposal Network for Nucleus Segmentation" has been accepted by TIP.
2022-10: Happy to be Top 2% Scientists Worldwide in the area of artificial intelligence & image processing, identified by Stanford University,
2022.
2022-09: One paper "RA Loss: Relation-Aware Loss for Robust Person Re-identification" has been accepted by ACCV.
2022-08: Be invited to serve as Area Chair for ICLR 2023
2022-07: Be invited to serve as Associate Editor for IEEE TIP.
2022-01: Be invited to serve as Area Chair for MICCAI 2022.