Bo Zhao

Bo Zhao is an Assistant Professor in the Department of Computing at Xi’an Jiaotong-Liverpool University, with a joint affiliation to the University of Oxford where he continues collaborative research in demographic sciences and population health. His career trajectory spans post-doctoral research at Oxford’s Nuffield Department of Population Health and earlier roles as Research Associate at the University of Leicester’s NIHR Respiratory Biomedical Research Unit.

Education:

• PhD in Computer Science and Informatics, Cardiff University (2011–2016)
• BEng in Communication Engineering, Wuhan University of Technology (2004–2008)

Research Interests:
Dr Zhao’s work sits at the intersection of computer science and population health. He develops computational methods for high-dimensional metabolomic data—especially breathomics—using advanced two-dimensional gas chromatography and mass spectrometry. A second major strand examines socio-economic determinants of respiratory disease, leveraging large-scale observational data to quantify how prepayment energy meters influence emergency hospital admissions and health inequalities.

Publications Overview:
His 2015–2024 portfolio reveals a clear evolution from foundational bioinformatics tooling (KneeTex NLP system, LabPipe data-management suite) through methodological advances in GC×GC data processing, and finally to high-impact epidemiological studies linking deprivation metrics with respiratory health outcomes. The translational 2022 Science Translational Medicine paper showcases breath-metabolite signatures for acute cardiorespiratory diagnosis, illustrating the clinical relevance of his analytical innovations.

Grants, Awards & Students:
No specific grants, awards, or doctoral students are listed in the provided text.

Laboratories & Teams:
While no dedicated laboratory name is mentioned, his affiliations with the Nuffield Department of Population Health at Oxford and collaborative links to the Department of Sociology and Leicester’s NIHR Respiratory Unit imply active participation in multidisciplinary teams spanning epidemiology, analytical chemistry, and computational biology.