Strengthening security of drinking water infrastructure, VCU researchers receive support from Commonwealth Cyber Initiative
The $100,000 grant supports development of quantum-enhanced infrastructure monitoring methods
Helping to protect drinking water systems from critical infrastructure failures, Thang Dinh, Ph.D., associate professor in the Department of Computer Science at the Virginia Commonwealth University (VCU) College of Engineering, is developing quantum-enhanced monitoring methods to detect infrastructure flaws with support from a $100,000 Commonwealth Cyber Initiative grant.
“The Richmond water crisis in 2025 showed us traditional monitoring systems that watch one sensor at a time are not enough,” Dinh said. “Our project aims to use quantum computing to analyze hundreds of sensors simultaneously, so utilities can identify problems earlier and respond faster. This approach will be able to detect patterns of failure across a utility’s entire network.”
Water utilities nationwide face growing challenges from aging infrastructure, extreme weather and increasingly sophisticated cyber threats, according to organizations like the U.S. Environmental Protection Agency and Virginia Department of Health. Incidents across Virginia,like the James River Treatment Plant failure and Richmond water crisis, have underscored how quickly such vulnerabilities can disrupt service for large populations.
Led by Dinh with support from co-Primary Investigator Jayasimha Atulasimha, Ph.D., Engineering Foundation Professor in the Department of Mechanical & Nuclear Engineering at the VCU College of Engineering, and Laura Poe, Ph.D., assistant professor of information systems and cybersecurity at Longwood University, the project, named “Quantum-AI Detection of Cyber-Physical Attacks on Smart Water Networks,” is a collaboration that brings together expertise in quantum optimization algorithms, quantum device physics and cybersecurity.
The research will develop semi-quantum Restricted Boltzmann Machines, or sqRBMs, designed to identify mechanical failures, like burst pipes, and deliberate cyber manipulation of pumps and valves. By leveraging quantum annealing, researchers aim to overcome computational limits that constrain classical machine learning systems, enabling faster model training and more responsive monitoring. It builds on a strong foundation of prior work, like Dinh’s 2025 IonQ Research grant on quantum optimization and machine learning and 2025 Commonwealth Cyber Initiative grant on quantum-cloud security for cyber-physical systems. Dinh’s expertise is complemented by Atulasimha’s NSF-funded research on energy-efficient quantum control of robust spin ensemble qubits conducted in collaboration with UCLA.
Supporting two VCU Ph.D. students, one Longwood University master’s student and three undergraduates, the project will give students hands-on experience with quantum computing hardware, machine learning for cybersecurity and critical infrastructure systems. Researchers also plan to host a quantum computing workshop to help strengthen Virginia’s emerging quantum workforce.
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Categories Computer Science, Faculty Awards, Mechanical & Nuclear Engineering, Research Grants