Summary
Xian Yang is a research fellow and machine learning scientist with 13 years of experience applying deep learning, NLP and statistical methods to large-scale biomedical and clinical data. Based at Imperial College London after a research stint at Microsoft Research Asia, he leads development of NLP and DL approaches for phenotype annotation in electronic health records and has driven high-impact translational medicine projects including a royal-foundation study on mental health. He combines hands-on data engineering—building pipelines for high-throughput proteomics and lipidomics—with advanced modeling for unbiased biomarker discovery and population-scale analytics. His background spans a PhD in Computing Science from Imperial, an MSc with distinction in Digital Communication, and first-class engineering training, reflecting both theoretical depth and practical rigor. Notably, he has moved seamlessly between academic and industry research environments, translating novel algorithms into tools for real-world health data. He brings a rare blend of domain expertise in healthcare data, scalable ML, and conversational analytics that informs policy-relevant research.
13 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Computing Science, Doctor of Philosophy - PhD, Computing Science at Imperial College London
Master's degree, Digital Communication, Distinction, Master's degree, Digital Communication, Distinction at University of Bath
Bachelor's degree, Electrical, Electronics and Communications Engineering, First Class, Bachelor's degree, Electrical, Electronics and Communications Engineering, First Class at Huazhong University of Science and Technology
Chinese, English