Zeiad Mansour

Zeiad Mansour is a skilled software engineer with extensive experience in developing secure and efficient systems across various companies, including Abnormal AI and Rapid7. At Rapid7, significant contributions included leading the development and testing of endpoint components, achieving a 70% reduction in forensic data collection latency, and creating event-driven distributed microservices. Prior to Rapid7, Zeiad served as an R&D engineer at Queen's University, where innovative projects included a deep learning Yara rules generator that improved malware detection by 25% and designing an AI-driven intrusion detection system. Zeiad has also gained experience in data analytics and programming instruction, having taught Python courses to students. Zeiad holds a Master of Science in Computer Science from Queen's University and a Bachelor's degree in Computer & Communications Engineering from Cairo University.