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Nan Meng

Research Assistant Professor (HKU)

Principle Scientist of CONOVA

Manager of CONOVA (Beijing)

Co-director of Digital Health Laboratory

Department of Orthopaedics and Traumatology

Li Ka Shing Faculty of Medicine

The University of Hong Kong.

Nan Meng received his Ph.D. degree in 2020 in Electric and Electronic Engineering from The University of Hong Kong. At HKU, he conducted research for image-based cancer diagnosis and released the first large-scale dataset for human somatic bright-field cells. He also conducted research for Light Field Reconstruction in the Imaging Systems Laboratory, supervised by Prof. Edmund Y. Lam. During his PhD, he consulted for an AI company in the areas of multi-view imaging systems and HKU Medicine School about medical image processing and analysis. After graduation, Dr. Meng joined the Digital Health Laboratory in HKU as a postdoc for over 2 years to conduct research in intelligent orthopaedics. At present, he is a research assistant professor.


His research interests include computational optics and imag-ing, from algorithms to applications and medical image analysis. His research direction includes light-field reconstruction, view synthesis, depth estimation and medical imaging.

I am currently a senior researcher and engineer in HKU O&T Department, focusing on intelligent solutions for bone disease using deep learning techniques. I am mainly leading two medical projects, i.e., AlignPro and MSKAlign Wukong. We always welcome students, researchers, and engineers from different regions worldwide who have an interest in artificial intelligence techniques (deep learning, machine learning, etc) for real medical and clinical problems. We continue to recruit multiple research assistants and algorithm scientists.




AlignPro is a medical AI platform that supports automatic spine malalignment analysis. It Integrates customers'  radiographic spinal images for analysis and carries out personalized visualization results for doctors' reference.

MSKAlign Wukong


MSKAlign Wukong is a medical device that provides non-invasive and non-radiation care for the spine. Endowed with the advanced 3D depth sensing module and deep learning techniques, MSKAlign Wukong can obtain back geometry as well as quantify surface appearance with ease.

Medical LightField

Medical Light Field (MLF) aims to provide doctors with a new level of insight into the human body, aiding in the diagnosis and treatment of numerous medical conditions. For surgery, it provides surgeons with a more comprehensive view of the surgical site, allowing for more precise and efficient procedures.

NanMeng - Projects

Select Publication


Computer Science


[J] Meng, Nan and Cheung, Jason Pui Yin and Wong, Kwan-Yee Kenneth Wong and Dokos, Socrates and Li, Sofia Pik Hung and Choy, Richard W. and To, Samuel Ching Hang and Li, Ricardo J. and Zhang, Teng, "An Artificial Intelligence Powered Platform for Auto-Analyses of Spine Alignment Irrespective of Image Quality with Prospective Validation", Lancet: eClinicalMedicine, January 2022. (IF: 17.033)  

DOI: 10.1016/j.eclinm.2021.101252

[J] Meng, Nan and Cheung, Jason Pui Yin and Wong, Kwan-Yee Kenneth Wong and Moxin Zhao and Ashish Diwan and Zhang, Teng, "Radiograph-comparable image synthesis for spine alignment analysis using deep learning with prospective clinical validation", Lancet: eClinicalMedicineMay 2023. (IF: 17.033)  

[J] Nan Meng, Kai Li, Jianzhuang Liu, and Edmund Y. Lam, “Light Field View Synthesis via Aperture Disparity and Warping Confidence Map”, IEEE Transactions on Image Processing, March 2021. (IF: 11.041) 

DOI: 10.1109/TIP.2021.3066293

[J] Nan Meng, Hayden K.-H. So, Xing Sun, and Edmund Y. Lam, “High-Dimensional Dense Residual Convolutional Neural Network for Light Field Reconstruction”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, no. 3, pp. 873-886, March 2020. (IF: 24.314) 

DOI: 10.1109/TPAMI.2019.2945027

[J] Nan Meng, Edmund Y. Lam, Kevin K.-M. Tsia and Hayden K.-H. So, “Large-Scale Multi-Class Image-Based Cell Classification with Deep Learning”, IEEE Journal of Biomedical and Health Informatics, vol. 23, no. 5, pp. 2091-2098, 2019(IF: 7.021) 

DOI: 10.1109/JBHI.2018.2878878

NanMeng - Publication

Review Service

Biomedical, Medical, Clinical

IEEE JBHI (2019-2024), IEEE TMI (2021), PLOS ONE (2023-2024), Scientific Report (2023)

ISBI (2023-2024)

Lancet-eClinicalMedicine (2024)

Computer Vision

IEEE TIP (2019-2024), IEEE TCI (2019-2022), IEEE TNNLS (2023), IEEE TMM (2023), IEEE TCSVT (2023)

Computer Graphics

Pacific Graphics (2023)


OSA JOSA A (2021)


Springer SIVP (2021-2023), Springer TVCJ (2023), Computers in Biology and Medicine (2024)

Position Opportunity

Digital Health Laboratory (under O&T Dept, HKU) welcomes applications from high potential candidates with academic excellence, research ability and potential, and good communication, and interpersonal abilities for multiple research and engineering positions, including Research Assistant, Mphil, PhD and PostDoc Fellow. We are also looking for Algorithm Researchers, Algorithm Engineers, Data Scientists, and Technicians working in either Mainland (Beijing, Shenzhen) or Hong Kong.

If you have interest, please fill in the following information with your Résumé/CV (link) and apply. We will contact you!

First name*

Last name*




Thanks for application and we will contact you!

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