Summary
David Amar is an Assistant Professor and computational scientist with a decade-long track record bridging machine learning, causal inference, and biomedical data science. He completed a PhD in Computer Science at Tel Aviv University, held a research fellowship at the Simons Institute, and spent formative years as a postdoc and staff scientist at Stanford, producing first-author work across ML, Bayesian modeling, and multi-omics. His industry roles at D2G Oncology and insitro translate cutting-edge causal and deep learning methods into translational genomics and drug discovery pipelines. At Tel Aviv University he now spans CS, AI, medicine and sports science, uniquely positioning him to drive interdisciplinary projects from theory to applied personalized medicine. Known for combining rigorous mathematical modeling with hands-on biomedical data analysis, he often works at the intersection of algorithmic innovation and real-world clinical data.
10 years of coding experience
8 years of employment as a software developer
BSc MSc PhD Computer Science Computational Biology BSc MSc PhD, BSc MSc PhD Computer Science Computational Biology BSc MSc PhD at Tel Aviv University
Stanford University