Summary
Dani Livne is a computational biologist with eight years focused at the intersection of machine learning, bioinformatics and clinical genetics, currently driving research at RespirAI Medical. He combines a PhD in Bioinformatics and Machine Learning with a long software engineering pedigree—spanning roles from software architect to data scientist—enabling him to move models from research into reliable production. Dani has applied classical and deep learning methods to real-world problems such as web UX churn prediction, traffic optimization, and personalized marketing, and holds a US patent for unsupervised struggle detection. His background in cloud security, time-series Bayesian systems, and optimization gives him a rare blend of algorithmic rigor and product-minded delivery. Comfortable operating across academia, startups and global business expansion, he has lectured on AI and built SageMaker-based SDKs to streamline team workflows. Based in Israel, he brings both hands-on implementation experience and strategic insight into deploying ML solutions in regulated clinical contexts.
8 years of coding experience
23 years of employment as a software developer
Master's degree Business/Managerial Economics, Master's degree Business/Managerial Economics at Tel Aviv University
Doctor of Philosophy - PhD Life sciences Bioinformatics and Machine Learning, Doctor of Philosophy - PhD Life sciences Bioinformatics and Machine Learning at Bar-Ilan University
English, Hebrew, French