Hadar Cohen is a software engineer specializing in AI and machine learning, with a strong focus on building production-grade algorithms and scalable systems. He works at Red Hat, where he contributes to AI engineering initiatives, including model deployment and infrastructure on OpenShift.
Before joining Red Hat, Hadar worked as a data scientist and algorithms developer, leading the development of machine learning models for risk prediction, onboarding optimization, and identity verification.
Hadar holds a master’s degree in engineering from Ben-Gurion University, where his research focused on interpreting neural networks from an algorithmic perspective, with an emphasis on solving the Boolean Satisfiability Problem (SAT). His work bridges the gap between theoretical understanding and practical application of deep learning systems.
With a background spanning software engineering, signal processing, and AI explainability, Hadar brings a rigorous, systems-level approach to developing intelligent solutions.
