Prof David CC Lam is a material scientist who teaches mechanical engineering design, manufacturing and material processing at the Hong Kong University of Science and Technology (HKUST).  He conducts research in material processing and applies the research in the development of new medical devices for glaucoma, stroke (, vascular healing and new biosensors and diagnostic devices.  Working with clinicians and hospitals, he integrates data from advanced sensors developed from his research with big data available from partners to create AI decision support systems to improve diagnosis and treatment of ocular and vascular diseases.  He develops new sensors with industrial groups and incorporate the data from the sensing systems into processing systems to improve the intelligence and workings of manufacturing systems in industry.  He has been working with leading manufacturers to improve the fabrication processes and reliability of flexible electronics systems.  He has received multiple teaching development grants and developed new experiential and team-based peer-learning and teaching methodologies, courses.  He established the Electric Vehicle Research Group (EVRG) and an EV racing platform to enable experiential learning in UG and PG education.  Senior members of EVRG are applying sensors and AI to develop systems for distributed smart city EV charging and rescue for startups.


Teaching Activities

MECH3520 Design and Manufacturing II

Research Interests

Ocular medical devices [contact lens sensor (CLS); corneal indentation Device (CID)]
Endoluminal medical devices (rf thrombectomy devices; vascular healing devices)
AI systems (medical diagnostic and treatment; food processing; material processing)
Biosensing (Vascular obstruction; aneurysm detection)
Electric Vehicle (distributed smart grid charging and vehicle rescue)
Electronics packaging (processing and reliability of electronic systems on flexible substrates)

Research Projects

  • Advanced Stroke Treatment Technology Program 
  • Development of Wireless Contact Lens Sensor based Intraocular Pressure (IOP) Monitoring System for Clinical Diagnosis
  • Real-time monitoring technology for intraocular pressure in space flight
  • Development and Prototype Testing of an rF Mechanical Thrombectomy Device 
  • Development And Prototyping Of A Biomechanical Property-Based Diagnostic Technology For Glaucoma Diagnosis 
  • Research and development of statistical process-reliability relations on multilayerd flexible substrates