Dr. Robin Hofmeister | University of Lausanne | Switzerland
Dr. Robin Hofmeister is a highly skilled data analyst and statistical geneticist specializing in functional genomics and large-scale next-generation sequencing (NGS) analysis. With expertise spanning SNP arrays, exome, whole-genome, and RNA-seq data, he has contributed to cutting-edge genetic research using resources like the UK Biobank, Estonian Biobank, and Finngen. His work focuses on haplotype phasing, parent-of-origin inference, and genome-wide association studies (GWAS), integrating advanced computational tools and cloud platforms. Dr. Hofmeister’s career includes collaborations across leading European research institutes, numerous high-impact publications in Nature and Nature Genetics, and recognition through multiple international awards for excellence in human genetics research.
Profiles
Education
Dr. Hofmeister earned his Ph.D. in Quantitative Biology from the University of Lausanne, Switzerland, under Olivier Delaneau, focusing on haplotypes in complex trait genetics. He completed his M.Sc. in Molecular Life Sciences, specializing in bioinformatics, at the University of Lausanne, conducting projects on long non-coding RNA in breast cancer and detecting whole-genome duplications. His B.Sc. in Fundamental Biology emphasized advanced molecular, cellular, and developmental biology, as well as genetics and genome evolution. This multidisciplinary foundation in biology and computational methods underpins his ability to integrate genomics, bioinformatics, and statistical genetics in large-scale biomedical research.
Professional Experience
Dr. Hofmeister is currently a Visiting Research Fellow at the Institute for Molecular Medicine Finland and a Research Fellow in Epi- and Pharmacogenomics at the University of Tartu, Estonia. He also serves as a Research Fellow in Statistical Genetics at the University of Lausanne and University Center for Primary Care and Public Health. His past roles include visiting fellowships in Austria and Estonia, and a research internship in Lausanne. His expertise includes NGS data processing, phasing, imputation, GWAS, and eQTL analysis for large cohorts, alongside mentoring, teaching, and peer review for leading journals such as Nature Communications and PLOS Genetics.
Research Focus
Dr. Hofmeister’s research centers on statistical genetics, with particular emphasis on haplotype phasing, rare variant analysis, and parent-of-origin inference in large-scale human genomics datasets. Leveraging biobank resources such as UK Biobank, Estonian Biobank, and Finngen, he applies state-of-the-art computational tools to uncover genetic architecture underlying complex traits. His work integrates genome-wide association studies, expression quantitative trait loci mapping, and advanced statistical modeling to improve accuracy in genetic analyses. By combining high-performance computing, cloud platforms, and innovative algorithmic approaches, Dr. Hofmeister’s research advances the precision of genomic medicine and contributes to translating large-scale genomic data into actionable biological and clinical insights.
Awards and Honors
Dr. Hofmeister has received numerous prestigious awards, including the 2025 Early Career Award for Outstanding Science from the European Society of Human Genetics, the Best Oral Presentation Award at the European Mathematical Genetics Meeting, and multiple “Reviewers’ Choice” awards from the American Society of Human Genetics. He was a finalist for the Charles J. Epstein Trainee Award for Excellence in Human Genetics Research and earned departmental and institutional prizes for outstanding research output and teaching dedication. His work has also secured competitive funding, such as enhanced credits from the UK Biobank Research Platform, enabling large-scale genomic analysis and innovative methodological development.
Publications Top Notes
Noncoding rare variant associations with blood traits in 166,740 UK Biobank genomes
Journal: Nature Genetics
Authors: Diogo M. Ribeiro; Robin J. Hofmeister; Simone Rubinacci; Olivier Delaneau
Parent-of-origin effects on complex traits in up to 236,781 individuals
Journal: Nature
Authors: Robin J. Hofmeister; Théo Cavinato; Zoltán Kutalik
(The full author list likely includes many collaborators, but these are the lead names captured in the journal’s author summary.)
The role of common and rare genetic variation on adiposity across childhood
Authors: The specific author list did not appear in the sources available online, only the title and key findings were mentioned
Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank
Journal: Nature Genetics, Volume 55, Issue 7, pages 1243–1249
Authors: Robin J. Hofmeister; Simone Rubinacci; Diogo M. Ribeiro; Olivier Delaneau
Conclusion
Dr. Robin Hofmeister exemplifies the qualities of an innovative and impactful researcher in statistical genetics and functional genomics. His strong academic background, extensive international collaborations, and record of high-impact publications demonstrate his ability to drive scientific discovery. His pioneering work on haplotype phasing, parent-of-origin inference, and rare variant analysis addresses key challenges in human genetics. Recognized through multiple awards, fellowships, and invited talks at major conferences, Dr. Hofmeister continues to contribute meaningfully to the advancement of precision medicine. His blend of technical expertise, scientific vision, and collaborative leadership positions him as a leading figure in large-scale genomic research.