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Dr Ken (Kezhi) Li
UCL Institute of Health Informatics
222 Euston Road
London
NW1 2DA
Appointment
- Lecturer in Artificial Intelligence in Healthcare
- Institute of Health Informatics
- Faculty of Pop Health Sciences
Research Summary
Ken (Kezhi) Li is a lecturer (Assistant Professor) of AI in Healthcare, at Institute of Health Informatics (IHI), University College London (UCL). He is passionate about solving physiological, medical, clinical, operational problems in healthcare using AI techniques. Specifically, he has expertise in
AI in healthcare
Biomedical time series analysis using monitors/wearables
Diabetes management
Patient flow optimization
Prediction and risk management using clinical data
Dr. Li has published over 80 research papers in leading journals (total IF>300) and conference proceedings including
IEEE: IEEE Journal of Biomedical and Health Informatics, IEEE Internet of Things Journal, IEEE Sensors Journal; IEEE Trans on Signal Processing, IEEE Trans on Automatic Control, IEEE Trans on Cybernetics, IEEE Trans on Wireless Communications, etc;
Clinical: Nature Methods, NPJ Digital Medicine, Diabetes Technology & Therapeutics, Alzheimer's & Dementia, Heart, BMJ, JAMIA, etc
Physics: Scientific Reports, Physical Review A, etc
AI/Data conference: NeurIPS, IJCAI, CHI, ICASSP, ISCAS, BioCAS, ITW, IFAC, etc.
Teaching Summary
He is the director of MRes study (UKRI UCL Centre for Doctoral Training in AI-enabled Healthcare Systems) and the Module leader of:
CHME0032: Healthcare Artificial Intelligence Journal Club (19-23)
CHME0033: Dissertation in Artificial Intelligence Enabled Healthcare (19-23)
CHME0035: Advanced Machine Learning for Healthcare (20-23)
CHME0016: Machine Learning in Healthcare and Biomedicine (19-20)
He also has been engaging in the module
CHME0016: Machine Learning in Healthcare and Biomedicine (20-21)
CHME0021: Dissertation in Health Data Science (19-23)
CHME0018: Machine Learning in Health Care (19-23)
CHME0020: Dissertation in Health Data Analytics (19-23)
Other Teaching in
CHME0030: Health Analytics Principle (HAP) 2021-2023
UCL Data Science in Healthcare Summer School 2022
Prior to joining UCL, he has experience in teaching/demonstrating courses in Python, machine learning, advanced machine learning, computer vision, image processing, statistical signal processing, matlab, information theory, control theory, delphi, etc.
Appointments
| 2017 – 2019 | Senior Research Associate | Imperial College London, United Kingdom | |
| 2015 – 2017 | Postdoctoral Research Scientist | Medical Research Council, United Kingdom | |
| 2014 – 2015 | Research Associate | University of Cambridge, United Kingdom | |
| 2013 – 2014 | Research Fellow | Royal Institute of Technology (KTH), Sweden |
Academic Background
| 2013 | Doctor of Philosophy | Imperial College of Science, Technology and Medicine |
