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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.
New: I am looking for PhD students funded by A*STAR
AGS and SINGA to work on Multi-modal Medical LLM for Healthcare and Automatic Diagnosis
with distinguished Professor from NTU
Research Interest:
Computer Vision: 3D Vision, Robust Vision and Perception
Imaging: Low Light Imaging
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 Graduate Scholarship: A*STAR Graduate Scholarship supports Singapore students who wish to pursue their PhDs from Singapore Universities (NUS, NTU, and SUTD).
A*STAR SINGA: A*STAR SINGA Scholarship supports international students who wish to pursue their PhDs from Singapore Universities (NUS, NTU, and SUTD).
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.
Research Interns:
Looking for research intern students for projects.
2023-03: One paper "Perceptual Quality Assessment of Enhanced Colonoscopy Images: A Benchmark Dataset and An Objective Method" has been accepted by TCSVT.
2023-03: Be invited to serve as Area Chair for NeurIPS 2023.
2023-01: Be invited to serve as Area Chair for MICCAI 2023.
2023-01: One paper "CLC-Net: Contextual and Local Collaborative Network for Lesion Segmentation in Diabetic Retinopathy Images" has been accepted by Neurocomputing.