Ying Wang Receives $360K U.S. Army Research Office Early Career Award

Ying Wang, associate professor in the Department of Systems Engineering at Stevens Institute of Technology, has received a $359,951 Early Career Program award from the U.S. Army Research Office (ARO) for her project, “From Proactive to Autonomous: Dynamic Assurance in CPS via Formal-Fuzz Interactions and Posterior Formal Verification.”

A recipient of the prestigious Defense Advanced Research Projects Agency (DARPA) Young Faculty Award, Wang is pioneering approaches for autonomous systems — such as drones, self-driving vehicles and defense control networks — to continuously check and improve their own safety and security in real time.

My research focuses on developing provable and scalable assurance methods that verify safety, security and reliability under changing conditions to keep autonomous systems and command-and-control networks secure and dependable. We are working to understand how these complex systems can maintain trust and reliability.

By combining rigorous mathematical proofs with smart testing that explores unexpected situations, her approach aims to ensure these systems can operate reliably, even in unpredictable, real-world conditions. 

As cyber-physical systems (CPS) — which connect software with physical processes such as transportation, energy and defense — grow increasingly complex, they also face more advanced cyber threats. Traditional testing and verification methods are often limited in their ability to scale.

To address those concerns, Wang’s project combines powerful tools to find weaknesses early, adapt to new threats in real time and keep systems strong. 

“My research focuses on developing provable and scalable assurance methods that verify safety, security and reliability under changing conditions,” she said, “to keep autonomous systems and command-and-control networks secure and dependable. We are working to understand how these complex systems can maintain trust and reliability.”

A continuous loop of learning and assurance

Professor Ying Wang Wang’s project integrates three complementary tools: formal verification, intelligent fuzz testing, and causality modeling. Formal verification uses rigorous mathematics to ensure a system is built correctly. Intelligent fuzz testing introduces unexpected or random situations to help the system learn. Causality modeling helps reason and predict how likely given outcomes are so systems can make secure decisions in uncertain environments. 

“It’s a continuous feedback cycle where formal analysis guides where to test, and fuzz testing results refine what to verify,” Wang explained. “This connects mathematical reasoning with real-world evidence, helping systems uncover hidden issues.”

This continuous assurance cycle strengthens system resilience, helping critical platforms such as command-and-control systems, aerospace networks, autonomous vehicles and smart infrastructure detect and respond to emerging risks as they occur.

From research insights to real-world innovation

Wang’s previous DARPA-funded theoretical work on formal assurance for large-scale, complex 5G systems laid the foundation for this research. 

“Through that work, we made strong progress in both theoretical development and technology transition,” she noted, “The experience guided us to look deeper toward provable assurance, inspiring the next stage of research on building scalable, adaptive and autonomous assurance systems.”

Next up, Wang’s group will explore how these assurance methods can extend across the entire lifecycle and supply chain of cyber-physical systems, addressing technical, regulatory, and policy challenges that influence system trust and performance.

Wang encourages up-and-coming systems engineers to get involved.

“This is an exciting and challenging field with so much to explore,” she said. “Don’t be discouraged by the complexity — that’s what makes it interesting.”