Eilis Hannon

Eilis Hannon is an Associate Professor in Bioinformatics in the Complex Disease Epigenetics Group at the University of Exeter Medical School, and holds an EPSRC Research Software Engineering Fellowship. She trained as a mathematician and has over thirteen years of experience developing statistical and computational approaches for analysing genomic, transcriptomic, and epigenomic data. Much of her work focuses on understanding gene regulation in the context of brain and neurodevelopmental disorders, with an emphasis on integrating multiple layers of genomic information to investigate how genetic risk contributes to complex disease.

Her research includes the development of integrated genomics approaches to explore the functional consequences of disease-associated genetic variants, as well as contributions to large-scale collaborative efforts. She leads the development team for the international Genetics of DNA Methylation Consortium and has contributed methods, standards, and software tools used in epigenetic epidemiology. Recent projects focus on computational alternatives to experimental cell isolation, including approaches for deriving cell-type-resolved epigenetic information directly from bulk tissue data. She also serves as Chief Data Officer for the UK Human Functional Genomics Initiative, where she helps shape data strategy, infrastructure, and standards to support collaborative functional genomics research across the UK.

She is actively involved in advancing research software quality, data stewardship, and reproducibility as a Fellow of the Software Sustainability Institute. At Exeter, she established the Coding for Reproducible Research training programme, which provides skills development in open and reproducible research practices for staff and students. This work has informed her interest in data science pedagogy and contributed to her receiving a Skills Policy Award from the Alan Turing Institute.

She contributes to data science education, research culture, and capacity building through several leadership roles, including Institutional Reproducibility Lead, Data Science Lead for the MRC-funded GW4 BioMed DTP, and Module Lead for Statistics for Health and Life Sciences and Mathematics for Data Science.