Biography
Ngai-Man (Man) Cheung is an Associate Pillar Head and Associate Professor with Singapore University of Technology and Design (SUTD). He received his PhD degree in Electrical Engineering from University of Southern California (USC), Los Angeles, CA. His PhD research focused on image and video coding, and the work was supported in part by NASA-JPL. He was a postdoctoral researcher with the Image, Video and Multimedia Systems group at Stanford University, Stanford, CA.
He was a core team member of the Foundational Research Capabilities Team for AI – National Research Foundation (NRF) Singapore, and an AI Advisor for Smart Nation and Digital Government Office (SNDGO) in Singapore. His research has resulted in more than 100 papers and 14 US patents granted with several pending. Two of his inventions have been licensed to companies. One of his research results has led to a SUTD spinoff on AI for healthcare: . His research has also been featured in the .
As a long-time member of the IEEE Signal Processing Society, he has been deeply engaged in the signal processing community. He currently serves as Senior Area Editor for both the IEEE Transactions on Image Processing and the IEEE Signal Processing Letters, and as Associate Editor for the IEEE Transactions on Multimedia and APSIPA Transactions on Signal and Information Processing. He is the Lead General Chair of IEEE VCIP 2026 and has held key roles in other major signal processing and AI conferences. Additionally, he is a Founding Committee Member of the APSIPA Singapore Chapter. Since 2015, he has served in multiple executive roles in the IEEE Signal Processing Society – Singapore Chapter, including Chapter Chair.
He has received several research recognitions, including the Best Paper Finalist at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019, the Finalist of Super AI Leader (SAIL) Award at the World AI Conference (WAIC) 2019 at Shanghai, China. His research interests are Signal and Image Processing, Computer Vision and AI.
Research interests
- Signal and Image Processing
- Computer Vision
- AI
Selected scientific awards and recognitions
- Featured Certification, Transactions on Machine Learning Research (TMLR) 2025
- Best Submission Finalist, AI Health World Summit 2025
- Best Paper Finalist, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 (selected from over 5000 submissions)
- Finalist, Super AI Leader (SAIL) Award, World AI Conference (WAIC), Shanghai, China, 2019 (selected from over 700 submissions worldwide)
- Excellence in Research Award, SUTD 2018
- First Prize, Accenture HealthTech Challenge (Singapore) 2018
- Best Design Award, MIT Hacking Medicine@SG (HackMed) 2015
- Best Poster Award, IEEE Life Sciences Grand Challenges Conference 2013
- Best Student Paper Award, 20th IEEE International Conference on Image Processing (ICIP) 2013 (Total 2102 submissions)
- Honorable Mention, ACM Multimedia Open Source Software Competition 2011
- Best Paper Finalist, IEEE Transactions on Circuit and System for Video Technology 2010
- Best Paper Second Place Award from VCIP 2008 (Visual Communications and Image Processing Conference)
- Best Research Paper Award Honorable Mention, USC Electrical Engineering 2008
- Best Paper Award Finalists at PCS 2007 (Picture Coding Symposium)
- Best Student Paper Award, IEEE MMSP 2007 (International Workshop on Multimedia Signal Processing)
- Best Paper Award, EURASIP Journal on Advances in Signal Processing 2006
Professional services
- Senior Area Editor, IEEE Transactions on Image Processing (2025 鈥 present)
- Senior Area Editor, IEEE Signal Processing Letters (2024 鈥 present)
- Associate Editor, IEEE Transactions on Multimedia (2021 鈥 present)
- Associate Editor, APSIPA Transactions on Signal and Information Processing (2022 – present)
- Key committee member of IEEE Signal Processing 鈥 Singapore Chapter (Chapter Chair: 2021 鈥 2022; Vice Chair: 2019 鈥 2020; Treasurer: 2025 鈥 2026; Secretary: 2023 鈥 2024, 2017 鈥 2018)
- Founding committee member of Asia Pacific Signal and Information Processing
- Association (APSIPA) Singapore Chapter
- APSIPA Distinguished Lecturer 2025 – 2026
- Key committee members in major international conferences (Lead General Chair in IEEE VCIP 2026, Technical Program Co-Chair in APSIPA ASC 2025, Lead Education Chair in IEEE ICASSP 2022, Area Chairs and Senior Program Committees in many conferences)
- IEEE Multimedia Systems and Application Technical Committee (MSA TC) (2020 – present)
- IEEE Senior Member
Selected media coverage
- Straits Times coverage of our Hypersense.ai technology:
- 8world interview of KroniKare:
Selected publications
- Guimeng Liu, Tianze Yu, Somayeh Ebrahimkhani, Lin Zhi Zheng Shawn, Kok Pin Ng, NM Cheung. How Do Medical MLLMs Fail? A Study on Visual Grounding in Medical Images. ICLR 2026.
- Ngoc-Bao Nguyen, Sy-Tuyen Ho, Koh Jun Hao, NM Cheung. Do Vision-Language Models Leak What They Learn? Adaptive Token-Weighted Model Inversion Attacks. CVPR 2026.
- Somayeh Ebrahimkhani, Guimeng Liu, Tianze Yu, Xuling Lin, Adeline Su Lyn Ng, Simon Kang Seng Ting, Shahul Hameed, Eng King Tan, Wing Lok Au, Kok Pin Ng, NM Cheung. Brain-FM: A Multimodal Foundation Model for Visual Question Answering in Brain Health Diagnostics. Alzheimer’s & Dementia, 2025.
- Viet-Hung Tran, Ngoc-Bao Nguyen, Son T Mai, Hans Vandierendonck, NM Cheung. Random Erasing vs. Model Inversion: A Promising Defense or a False Hope? Transactions on Machine Learning Research (TMLR) 2025. [Awarded Featured Certification, J2C Certification]
- Milad Abdollahzadeh, Touba Malekzadeh, Christopher TH Teo, Keshigeyan Chandrasegaran, Guimeng Liu, NM Cheung. A Survey on Generative Modeling with Limited Data, Few Shots, and Zero Shot. Transactions on Machine Learning Research (TMLR) 2025.
- Sy-Tuyen Ho, Tuan Van Vo, Somayeh Ebrahimkhani, NM Cheung. Vision Transformer Neural Architecture Search for Out-of-Distribution Generalization: Benchmark and Insights. NeurIPS-2024.
- CTH Teo, M Abdollahzadeh, X Ma, NM Cheung. FairQueue: Rethinking Prompt Learning for Fair Text-to-Image Generation. NeurIPS-2024.
- ST Ho, KJ Hao, K Chandrasegaran, NB Nguyen, NM Cheung. Model Inversion Robustness: Can Transfer Learning Help? CVPR-2024.
- Ngoc-Bao Nguyen (*), Keshigeyan Chandrasegaran (*), Milad Abdollahzadeh, Ngai-Man Cheung. Label-Only Model Inversion Attacks via Knowledge Transfer. NeurIPS-2023. (*) Equal contribution.
- Y Zhao, T Pang (*), C Du (*), X Yang, C Li, NM Cheung (*), M Lin, On evaluating adversarial robustness of large vision-language models. NeurIPS-2023. (*) Corresponding authors
- Christopher T.H Teo, Milad Abdollahzadeh, Ngai-Man Cheung. On Measuring Fairness in Generative Models. NeurIPS-2023.
- NT Tran, VH Tran, NB Nguyen, TK Nguyen, NM Cheung, “On data augmentation for GAN training” IEEE Transactions on Image Processing 30, 1882-1897. 2021. [Top-30 most cited paper in IEEE Transactions on Image Processing (TIP) by Google Scholar (out of more than 3400 papers published in TIP from 2020 to 2025)]
- H Le, TT Do, T Hoang, NM Cheung, “SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences,” in Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR-19) (Oral) (Total 5160 submissions) [CVPR-2019 Best Paper Finalist]