Simone Rubinacci

Simone Rubinacci is a Senior Researcher and Group leader at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, since September 2024, following postdoctoral fellowships at Harvard Medical School (2023-2024) and the University of Lausanne (2019-2022). Her academic foundation includes a DPhil in Statistics from the University of Oxford (2016-2020).

Her educational trajectory:

• DPhil in Statistics, University of Oxford (2016-2020)
• Postgraduate student, Systems Biology Doctoral Training Centre, University of Oxford (2015-2016)
• MSc in Computer Science, University of Milano-Bicocca (2012-2015)
• BSc in Computer Science, University of Milano-Bicocca (2009-2012)

Rubinacci pioneers statistical methods for large-scale genomic datasets, specializing in haplotype analysis and structural variation in human genomes. Her work extracts insights from noisy data like low-coverage sequencing and SNP arrays, directly addressing population structure and disease genetics. She bridges computational statistics with biomedical applications to decode genetic diversity and disease mechanisms.

Her 2024-2025 publications reveal intense focus on genomic data infrastructure: haplotype reference panels, imputation techniques, and polygenic risk scoring. Key innovations include SURFBAT for family-based association testing, UK Biobank imputation frameworks, and ancient DNA damage mitigation—collectively advancing precision genomics through computational rigor.

Major recognitions:

• Epstein Award Finalist, ASHG 2024
• Epstein Award Semifinalist, ASHG 2020
• Swiss National Science Foundation Postdoc.Mobility fellowship
• EPSRC PhD salary award

She has taught statistics and computer science at Oxford, Lausanne, and Milano-Bicocca. Current funding includes UK Biobank credits for haplotype phasing and her FIMM-EMBL project 'Integrating identity-by-descent and phasing to unveil novel insights on disease mechanisms' (2024-2029).

As FIMM-EMBL Group leader, she directs genomic methodology development within Helsinki's Faculty of Medicine and contributes to the university-wide DIVSOL-Humt profiling initiative for data-intensive societal research.