PROTON LAB
The Performance and Resource Optimization in Networks (PROTON) Lab focuses on developing advanced frameworks and methodologies for optimizing network performance, resource allocation, and system resilience across diverse application domains. Central to the lab's efforts is the creation of trust-aware and secure algorithms that enhance decision-making in autonomous and resource-constrained systems, such as GPS-denied navigation and cyber-physical infrastructures. The lab also emphasizes scalable solutions for real-time data fusion and resource management, leveraging machine learning and game-theoretic models to address the complexities of heterogeneous and distributed environments. Furthermore, PROTON Lab explores cutting-edge approaches for cybersecurity, renewable energy integration, and wireless communication systems, targeting practical challenges in smart grids, public safety, and sustainable energy systems. Through these multidisciplinary efforts, the lab contributes to the development of resilient, intelligent, and efficient networks capable of supporting next-generation technologies.
Associate Professor
School of Electrical, Computer and Energy Engineering
650 E Tyler Mall, Tempe, AZ 85281
Office: GWC 430
PROTON Lab: GWC 439
E-address: eirini@asu.edu
PhD Students
Positioning, Navigation, and Timing, Machine Learning, Communication Systems
(Post Proposal)
Public Safety Networks, Game Theory, Battlefield Communications and Rescue Operations
(Post Proposal)
Navigation Systems, Wireless Communications, Game Theory
(Pre qualifier)
Artificial Intelligence & Machine Learning
(Pre qualifier)
Low Altitude Economy, Industrial Internet of Things Testbed, Reinforcement Learning
(Pre qualifier)
Intelligent Power Systems, Game Theory, Reinforcement Learning
(Pre qualifier)
NextG Wireless Systems, IoT Industrial Testbed, Embedded Systems
(Pre qualifier)
PROTON Lab Research Portfolio
PROTON Lab Talks
June 2025, Dr. Tsiropoulou's Keynote at IEEE GreenNet Workshop, colocated with IEEE ICC 2025 is now live.
November 2025, Dr. Tsiropoulou's Talk at IEEE YP Webinar, ASU. Slides available here.