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As Director of Data Science, Eilon is leading the development of cutting edge machine learning, computational biology and statistical genetics approaches to improve drug development.

His team uses machine learning to integrate observations from large population-level studies with results from various high throughput in-vitro assays to identify potential drug targets.

Eilon has extensive experience in applying machine learning to decipher various biological questions. After completing a dual major B.Sc. in biology and computer science at Tel Aviv University, Eilon joined Rosetta genomics, where he worked on discovering miRNA genes in humans and predicting their targets. He then earned a PhD from the Weizmann Institute of Science under the supervision of Prof. Eran Segal. During his PhD, he developed synthetic biology Massively Parallel Reporter Assay (MPRA) and statistical and thermodynamic models, which he applied to decipher the encoding of transcriptional regulation in yeast. Following graduation, Eilon transitioned to a postdoc at Profs Jonathan Pritchard and Hunter Fraser labs in Stanford Medical school department of genetics. At stanford, Eilon worked on a diverse set of projects including: detection and fine mapping of genetic associations with T cell receptor V-genes expression; software for transplant health monitoring using cell-free DNA sequencing (which was commercialized by Stanford); and detection of functional genetic variants using a novel high throughput CRISPR editing. Eilon is the author of over 20 refereed publications appearing in venues such as Cell, Nature Biotechnology and Nature Genetics.

In his free time, Eilon enjoys hiking and camping outdoors with his family.