Kevin Andrea

Kevin Andrea is a full-time teaching-track Assistant Professor in the Department of Computer Science at George Mason University's College of Engineering and Computing. With a PhD in Computer Science from GMU, he teaches systems programming courses including Computer Systems and Programming (CS 367), Operating Systems (CS 471), and graduate-level Computer Systems and Fundamentals of Programming (CS 531). His research focuses on embedded systems, internet of things, and low-level programming, combining practical implementation with educational innovation.

• PhD, Computer Science, George Mason University (2023)
• MS, Computer Science, George Mason University
• BS, Computer Science, George Mason University
• AA, Computer Information Systems – Systems Programming, De Anza College

Andrea's research bridges hardware-software interactions through projects like resilient hierarchical routing for wireless networks and swarm robotics integration with sensor motes. His 2023 Resilient Hierarchical Routing for Wireless Networks and 2020 co-authored work on cross-disciplinary active learning strategies demonstrate his dual focus on technical innovation and pedagogical advancement.

His publications, including the 2017 MILCOM Best Paper Award-winning Multicast Address Moving Target Defensive System, reveal consistent contributions to network security and embedded systems. The 2014-2016 series on RPL-based protocols and swarm robotics establish foundational work in low-power networking and mobile sensor systems.

• Teaching Excellence Award, George Mason University (2025)
• Outstanding Term Assistant Professor, College of Engineering and Computing (2025)
• Outstanding Teaching Award, Department of Computer Science (2019-2020)
• Outstanding Mason Core Info Tech Ethics Course (2018)

As advisor for CS courses with extensive project components, Andrea emphasizes hands-on learning through Zeus Linux server-based assignments requiring strict compliance with academic integrity policies. He leads the Computer and Networking Systems (CNS) Lab and collaborates with the Autonomous Robotics Laboratory, applying systems programming principles to robotic platforms.