Research Projects
Artificial Intelligent light-based multi-target tracking and 3D visualisation

Programme(s) to which this project applies:

☑ MPhil/PhD ☒ MRes[Med] ☒ URIS

Surgical tracking is a fast-growing research field in both the academic and industrial worlds and may impact multiple aspects of surgery considerably, such as training, simulation, intraoperative decision-making, and the prediction of events and outcomes. This project aims to establish a radiation-free light-based surgical tracking device and develop a system embedded in the device to support its functions. We are looking for suitable candidates to assist with the device establishment and system development, surgical data collection and management, and real-time 3D reconstruction and visualization.

Our lab (Digital Health Lab) is involved in all aspects of scoliosis surgery research, including medical device development, deep learning algorithm or software development, 3D reconstruction and visualization of the spine, 3D display equipment development, AI-powered studies for predictive analytics, as well as clinical studies of novel treatment techniques.

Passionate students with backgrounds in clinical medicine, bioinformatics, computer graphics, computer science, computational modelling, biomechanics, etc, are welcomed to apply.

Dr T Zhang, Department of Orthopaedics and Traumatology

Dr Teng Grace Zhang 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 telemedicine, auto-diagnosis, surgical planning and tracking to facilitate real-time feedback with minimal radiations.

Currently,  Grace is an Assistant Professor, at the Digital Health Laboratory of the Orthopaedics and Traumatology Department, Clinical Medicine School, Faculty of Medicine, The University of Hong Kong (HKU). Previously, Grace has 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 in 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. Members of IEEE, EMBS, ABEC etc. The current ongoing projects include HMRF08192266 on light-based AI-driven malalignment quantification, HMRF19200911 on AIS digital health, PRP/078/21FX for surgical planning, AOSpine for automated spine malalignment screening, MRP/038/20X for non-radiation AI diagnosis and ITS/329/19 for anti-migration bone screws.  

HKU Scholars Hub

For more information or to express interest for this project, please email the supervisor or the specified contact point in the project description.  Interested candidates are advised to enclose with your email:

  1. your CV,
  2. a brief description of your research interest and experience, and
  3. two reference letters (not required for HKUMed UG students seeking MRes[Med]/URIS projects).

Information on the research programme, funding support and admission documentations could be referenced online at the Research Postgraduate Admissions website. General admission enquiries should be directed to

HKUMed MBBS students interested in the Master of Research in Medicine (MRes[Med]) programme may visit the programme website for more information.  

HKUMed UG students interested in the Undergraduate Research Internship Scheme (URIS) may visit the scheme’s website for more information.