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Teng Grace Zhang

Assistant Professor

 

Coordinator of Translational Research, PhD,MBME., BMed

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

Dr Teng Grace Zhang is currently an Assistant Professor and Coordinator of Translational Research of the Department of Orthopaedics and Traumatology, at The University of Hong Kong, who came to Hong Kong and founded the Digital Health Laboratory in 2018.

 

Grace is a biomedical engineer with a medical background. Most of Grace’s research combines both disciplines by focusing on the modelling of biological systems with direct clinical applications, including digital health, auto-diagnosis, optimised treatment planning and tracking to facilitate real-time feedback with minimal harm and improved outcomes. 

 

Previously, Grace worked for nearly seven years as a Scientific Officer at the St George Clinical School of the University of New South Wales (UNSW), Sydney, Australia. All Grace’s tertiary education, including her PhD (Australian Postgraduate Award) was completed at UNSW. Grace also has experience running multiple instruments and drug trials funded by Medtronic and Sigma. She’s experienced in managing a new system developed as she worked in Kunovus Australia for two years as a system engineer prior to coming to the University of Hong Kong—senior members of IEEE and EMBS, as well as members of AO and ISSLS, etc. The current ongoing projects include HMRF19200911 on AIS digital health, HMRF21223141 on AI management of MSK disorders, PRP/078/21FX for surgical planning, ITS/286/22FP for AI-assisted Bone tumour treatments and other RGC/NSFC supports. Academic metrics consist of h-index: 24; citations: 1702; supervise/cosupervise 11 research students; and over ten academic/industrial awards.

Completed funded projects:

HMRF08192266 on light-based AI-driven malalignment quantification;

ITS/329/19 for anti-migration bone screws;

MRP/038/20X for non-radiation AI diagnosis;

AOSpine for automated spine malalignment screening

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Publication

Publication / Junior

Meng N, Wong KYK, Zhao M, Cheung JPY, Zhang T*

2023, Radiograph-comparable image synthesis for spine alignment analysis using deep learning with prospective clinical validation. Lancet: eClinicalMedicine, 61, doi: 10.1016/j.eclinm.2023.102050

Meng N, Cheung JPY*, Wong KYK, Dokos S, Li S, Choy RW, To S, Li RJ, Zhang T*

2022, An artificial intelligence powered platform for auto-analyses of spine alignment irrespective of image quality with prospective validation, Lancet: eClinicalMedicine: 43

Li Y*, Zhang Y, Cui W, Lei B, Kuang X, Zhang T

2022, Dual Encoder-based DynamicChannel Graph Convolutional Network with Edge Enhancement for Retinal Vessel Segmentation, IEEE Transactions on Medical Imaging, doi: 10.1109/TMI.2022.3151666

Chen X, Lyu P, Han W, Yang L, Jin Y, Zhang T*, Shen J

2025, MPLDM: Multi-modal Prosthetic Loosening Diagnostic Model for Total Hip ArthroplastyTitle. Medical Image Analysis. 23:103921

Zhao M, Meng N, Cheung JPY, Tang CYK, Yu C, Zhong W, Lu P, Shi C, Zhuang Y, Zhang T*

2025, LatXGen: Towards Radiation-Free and Accurate Quantitative Analysis of Sagittal Spinal Alignment Via Cross-Modal Radiographic View Synthesis, IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2025.3613010

Fundings & Grants

Grant and Industrial Records

2024/12 - 2027/11

PI of HMRF 2023/2024 21223141 A multi-center prospective validation of ‘MSKalign’ digital low back pain management platform enabling AI auto-evaluation, personalized physiotherapy prescription, and dynamic disease progression prediction

2024-2026

PI of ITC ITS/286/22FP Artificial Intelligence Aided Surgical Planning System for Malignant Bone Tumour Excision with Intraoperative Safety Monitoring

2023-2026

PI of NSFC Young Scientists Fund 2023 82303957 Study of robust spine tumour excision surgical auto-planning and safety monitoring system

2023-2025

PI of HMRF 2021/2022 19200911 A multi-center prospective validation of ‘SpineNets’ virtual spinal evaluation platform enabling non-contact AI auto-diagnosis and follow-up of spine malalignment

2022-2024

PI of NSFC/RGC Joint Research Scheme project (N_HKU753/21) Mechanism research of borosilicate bioactive glass modulating the microenvironment of bone regenerative and inhibiting on the bone tumors, (HK$ 1,185,561)

2022-2025

PI of ITC PRP/078/21FX A Radiation-free Artificial Intelligence Spine Surgery Planning System with Biomechanical Analysis of Fixation Stability

2021-2022

PI of HMRF 08192266 Clinical validation of a novel system enabling non-radiation spinal deformity prediction using a combination of artificial intelligence and depth sensing technologies

2021/06 - 2023/05

Co-I and project manager of ITC MRP/038/20X A Non-radiation Artificial Intelligence 
Spine Deformity Diagnosis System

Awards and Translational Medical Research

2025

Asia Pacific Biomedical Engineering Consortium (APBEC) Young Scholar Award

2025

Gold Medal International Exhibition of Inventions of Geneva

2024

雄才杯創新創業大賽 優秀獎

2023

全球人工智慧產品應用創新創業大賽 (DEMO CHINA)人工智慧星銳賽 二等 獎

2022

Gold and Silver Medals International Exhibition of Inventions of Geneva

2017

iGlobal Sino-Australia Innovation & Entrepreneurship Competition 1st prize

2017

Zhongguancun Entrepreneur Competition ANZ region first prize

IEEE Senior member, CDHC 數字醫療委員會Committee, COITA 骨科創新與轉化專 業委員會 Committee

PI of more than 20 research grants (over HK$40 million from Innovation and Technology Commission, Research Grants Council, National Natural Science Foundation of China, and Health and Medical Research Fund)

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AIMED

We dedicate ourselves to non-invasive and intelligent solutions for spine care with advanced equipment and deep learning techniques. We are open and welcoming partners, researchers, engineers, etc worldwide.

Navigation

Availability

Monday-Friday:
9:30AM ~ 6:30PM

 

Post Address

Level 5, Professorial Block, Queen Mary Hospital, Pok Fu Lam, Hong Kong SAR, China

Call Number

+852 3917 6987
+852 6067 1846

@ aimed 2024. All Right Reserved.

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