Dr. Francesco Paolo Casale

Academic Career and Research Areas

Francesco Paolo Casale studied physics at the University of Naples Federico II, Italy. He received his PhD in statistical genetics at the University of Cambridge and the European Bioinformatics Institute in 2016, where he developed new computational methods for genetic association studies and contributed to landmark international projects such as the last phase of the 1000 Genomes Project and the Blueprint initiative. He conducted his postdoctoral studies at the Microsoft Research New England lab in Boston, working on deep generative models for imaging genetics and automated machine learning. In 2019, he joined insitro, a drug discovery and development company located in the bay area. There, he led the statistical genetics team, working at the interface of human genetics, machine learning and functional genomics to enable target identification and characterization. Since January 2022, he is a Principal Investigator in Machine Learning in Biomedicine at the Helmholtz Zentrum Munich at the Institute Helmholtz AI for Health and Helmholtz Pioneer Campus.

Francesco Paolo Casale’s research interests lie in computational methods to study the molecular underpinnings of complex traits, with a focus on human health and disease. His research group uses machine learning and statistical approaches to effectively leverage large-scale multi-modal datasets. Current major research areas are the development of scalable tools for genetic association studies, deep learning models for the joint analysis of medical imaging and genetic data, and computational methods to infer disease subtypes.

Awards

 -Highly Recognized article in PLoS Genetics Research Prize (2018)
- Microsoft Research postdoctoral fellowship (2017)
- EMBL studentship (2012)
- MSc and BSc degrees with honors (2009, 2012)