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Dr. Sai Kit Edmond Lam

Dr. Sai Kit Edmond Lam

Research Assistant Professor

Department of Biomedical Engineering

Biography

Dr. Lam is currently a Research Assistant Professor (RAP) in the Department of Biomedical Engineering (BME) at The Hong Kong Polytechnic University (PolyU). He received his B.Sc. degree in Applied Physics from City University of Hong Kong in 2014 where his research focused on biophysics of alpha-particle in zebrafish embryos via radiation-induced bystander effect. He then obtained his M.Sc. degree in Medical Physics from Duke University in 2017 where he worked on investigating effects of combining radiotherapy and immune checkpoint blockade, known as Radioimmunotherapy, on lung metastasis using mouse model of breast cancer. Dr. Lam further received his Ph.D. degree in Medical Physics from PolyU in 2022 where he investigated potential of multi-omics from routine radiotherapy data in prediction adaptive radiotherapy eligibility in patients with nasopharyngeal carcinoma. In addition to the academic journey, Dr. Lam has gained exposure in a medical imaging centre as a magnetic resonance imaging technologist, and in a world-leading innovator of precise radiation therapy solutions for managing cancer patients, Elekta Instrument Limited, as a research physicist.

Education and Academic Qualifications

  • Ph.D. in Medical Physics, The Hong Kong Polytechnic University
  • M.Sc. in Medical Physics, Duke University
  • B.Sc. in Applied Physics, City University of Hong Kong

 

Academic and Professional Experiences

  • Research Assistant Professor, Department of Biomedical Engineering, HK PolyU (2022-Present)
  • Research Assistant, Department of Health Technology & Informatics, HK PolyU (2018-2019)
  • Research Physicist, R&D Department, Elekta Instrument Limited, SH & BJ, China (2017-2018)
  • Magnetic Resonance Imaging Technologist, Centrum MRI Centre Limited, HK (2014-2015)

Research Interests

  • Adaptive radiotherapy
  • Ageing-related diseases
  • Artificial intelligence
  • Big data analytics
  • Cancer management
  • Deep learning
  • Medical image processing
  • Radiomics

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