Summary
Kezhi (Ken) Li is an Associate Professor of AI in Healthcare at UCL with 11 years of experience applying machine learning, signal processing and biomedical engineering to clinical problems. He leads the MRes CDT in AI-enabled healthcare systems and teaches advanced ML while directing research on EHR analytics, biomedical time-series from monitors and wearables, diabetes management, and LLM applications in mental health. His background spans top academic labs (Imperial, Cambridge, KTH) where he developed compressed sensing, deep learning (CNN/RNN/LSTM) and imaging algorithms, giving him a rare blend of theoretical rigour and practical deployment experience. Kezhi is also active in digital health topics like patient flow optimization and federated learning, and his work has attracted mainstream media attention. Colleagues describe him as a problem-driven researcher who moves fluidly between signal-level methods and system-level healthcare impact.
11 years of coding experience
6 years of employment as a software developer
PhD, Electrical and Electronic Engineering, PhD, Electrical and Electronic Engineering at Imperial College London
Bachelor, Electrical Engineering, Bachelor, Electrical Engineering at University of Science and Technology of China
University of Cambridge
Hong Kong University of Science and Technology (HKUST)
Secondary school, Secondary school at Hefei No.1 High School
English, Chinese