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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:
AI for Imaging: AI-enhanced Imaging, Low Light Imaging
AI for Biomedical and Healthcare: Medical Image Registration, Medical Image Analysis and Understanding
Computer Vision: 3D Vision, Robust Vision and Perception, Multimodal Foundational Models
Machine Learning: Trustworthy AI, Unserpervised Learning, Multimodal Data Learning, Learning With Less Data
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.
Yang Yu, Jiahao Wang, Weide Liu, Ivan Ho Mien, Pavitra Krishnaswamy, Xulei Yang, Jun Cheng Multimodal multitask similarity learning for vision language model on radiological images and reports
Neurocomputing, 2025.
Rui Gong, Kim-Hui Yap, Weide Liu, Xulei Yang, Jun Cheng Rectification-specific Supervision and Constrained Estimator for Online Stereo Rectification
CVPR, 2025.
Yi Zhou, Thiara Sana Ahmed, Meng Wang, Eric A. Newman, Leopold Schmetterer, Huazhu Fu, Jun Cheng, Bingyao Tan Masked Vascular Structure Segmentation and Completion in Retinal Images
TMI, 2025.