Kevin Yuan
CDT Student
I was born and raised in Germany, where I received my joint BSc. degree in Bioinformatics from the Ludwig-Maximilians-Universität München (LMU) and the Technical University of Munich (TUM) in 2020. My Bachelor's Thesis was on linking gene expression data to transcription factor binding information, to find transcription factors which are active during lactation by predicting gene expression from ChIP-seq signals.
During my undergraduates, I gained further practical experience while working as a student research assistant at the Chair of Experimental Bioinformatics at the TUM. Throughout the two years I worked on projects in the field of systems biology and systems medicine where I wrote tools and co-authored papers on (1) exploring the SARS-CoV-2 virus-host-drug interactome for drug repurposing, (2) analyzing the functional role of alternative splicing in protein interactions, and (3) network-constrained biclustering of patients and omics data.
My current research interests lie in the application of machine learning on health data and range from the fields of genomics to sensor data for medical applications - but I am always eager to explore new research areas.
In my free time I like to meet-up with friends, cook and build stuff; projects that I am currently working on can be found on my GitHub page: github.com/kevihiiin
Recent publications
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Interplay between C-reactive protein responses and antibiotic prescribing in people with suspected infection
Journal article
Gu Q. et al, (2025), BMC Infectious Diseases
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Machine learning and clinician predictions of antibiotic resistance in Enterobacterales bloodstream infections.
Journal article
Yuan K. et al, (2024), The Journal of infection, 90
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Predicting individual patient and hospital-level discharge using machine learning.
Journal article
Wei J. et al, (2024), Communications medicine, 4
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Distinct patterns of vital sign and inflammatory marker responses in adults with suspected bloodstream infection.
Journal article
Gu Q. et al, (2024), The Journal of infection, 88
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Changes in the investigation and management of suspected myocardial infarction and injury during COVID-19: a multi-centre study using routinely collected healthcare data.
Journal article
Chammas L. et al, (2024), Frontiers in cardiovascular medicine, 11