Summary
Joseph Kuo is a leading bioinformatician with 12 years of experience applying computational and statistical methods to large-scale NGS datasets, from bulk RNA-Seq and ChIP-Seq to ATAC-Seq and single-cell assays. Based at Uniklinik RWTH Aachen, he architects analysis infrastructure, advises on experimental design, and embeds into clinical research projects focused on applications like measurable residual disease in AML. He combines a PhD in Computational Biology with hands-on expertise in Python, R, TensorFlow/Keras and bespoke regulatory genomics toolboxes to turn complex genomic signals into actionable insights. Known for building end-to-end workflows and machine learning models (classification, clustering, regression) for genomics, he also translates results for both technical teams and clinical stakeholders. Beyond academia, his background spans project management, hands-on lab work in algal cultivation, and even service as a chemical specialist, reflecting a practical, multidisciplinary approach to problem solving. He describes himself simply as a computational biologist who likes to ask questions about life — a curiosity that drives rigorous, translational work in drug discovery and personalized medicine.
12 years of coding experience
5 years of employment as a software developer
Bachelor of Science (B.Sc.) Biology General, Bachelor of Science (B.Sc.) Biology General at National Taiwan University
Doctor of Philosophy - PhD Computational Biology, Doctor of Philosophy - PhD Computational Biology at RWTH Aachen University
English, Chinese, German