Len Daws

Len Daws serves as an Adjunct Professor in the Department of Computer Science at Rowan University's College of Science & Mathematics while concurrently holding a Sr. Engineering Manager position at Lockheed Martin in Moorestown, NJ. With over 12 years of teaching experience across New Jersey state and community colleges, he is currently in his sixth year instructing the Computers & Society course at Rowan University, focusing on large-scale software system development and integration.

His research specializes in machine learning robustness under adversarial conditions, particularly addressing noisy label learning challenges and cybersecurity threats in AI systems. Key contributions include modeling label noise dependencies across multiple annotators, developing contributor-aware defenses against backdoor attacks, and analyzing fundamental trade-offs between attack strength and detectability in adversarial settings.

Analysis of his publication history reveals a consistent trajectory toward securing machine learning pipelines against sophisticated threats, with recent work emphasizing labeler-dependent noise modeling and spectral ranking techniques for truth extraction from unreliable sources. His scholarship bridges theoretical machine learning with practical defense mechanisms for real-world AI deployment.