Nan Meng

Principle Scientist of CONOVA

Manager of CONOVA (Beijing)

Senior Researcher and Engineer (HKU)

Co-director of Digital Health Laboratory

Department of Orthopaedics and Traumatology, Medicine School, the University of Hong Kong.

Nan Meng received his B.S. degree (with distinction) in 2015 in Computer Science from the University of Electronic Science and Technology of China (UESTC), and 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 Imaging Systems Laboratory supervised by Prof. Edmund Y. Lam. During his Ph.D., he has 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 researcher and engineer.

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.

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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.

Projects

AlignPro

TM

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

TM

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.

 

Select Publication

Clinical

Computer Science

Bioinformatics

[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" [Under Review]  

[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

 

Review Service

Biomedical

IEEE JBHI (2019-2022), IEEE TMI (2021)

Computer Vision

IEEE TIP (2019-2022), IEEE TCI (2019-2022)

Optics

OSA JOSA A (2021)

Others

Springer SIVP (2021)

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!

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Thanks for application and we will contact you!