David Mohaisen

David Mohaisen is a Professor of Computer Science at the University of Central Florida with joint appointments in Computer Engineering and Modeling and Simulation. He directs the Security and Analytics Lab and has held prior academic positions at the University at Buffalo and Verisign Labs, alongside visiting roles at the U.S. Air Force Research Laboratory and Georgia Institute of Technology.

Education

• Ph.D. in Computer Science, University of Minnesota

Research Interests

Mohaisen's work centers on cybersecurity and analytics, with deep expertise in AI/ML security, blockchain systems, and networked infrastructure protection. His research spans robustness analysis of machine learning models, consensus protocol vulnerabilities in distributed systems, and threat intelligence for cyber-physical environments including AR/VR platforms. He addresses critical security gaps in emerging technologies through empirical measurements and theoretical frameworks.

Scientific Awards

His accolades reflect excellence across research, teaching, and service domains:

• Faculty Excellence in Mentoring Doctoral Students, UCF (2025)
• Best Paper Award, WISE (2024)
• ACM Distinguished Speaker (2024–2027)
• Teaching Incentive Award and Excellence in Graduate Teaching Award, UCF (2022)
• Research Incentive Award, UCF (2022)
• Editorial Excellence Award, IEEE TPDS (2022)
• Multiple best paper awards including IEEE Systems Journal (2020), ACM DLoT (2018), and WISA (2014)
• U.S. Air Force Visiting Faculty Research Award (2017)

Advising and Professional Service

Recognized for exceptional doctoral mentorship, Mohaisen actively shapes academic discourse through program committee leadership at top security conferences and editorial board service for IEEE publications. His professional engagement extends to ACM Distinguished Speaker and IEEE Distinguished Visitor roles, demonstrating significant community impact.

Labs and Research Teams

As director of the Security and Analytics Lab, he leads interdisciplinary teams investigating security vulnerabilities in AI systems, blockchain networks, and cyber-physical infrastructures. The lab emphasizes practical threat modeling and defensive solutions for real-world systems.