CCI Fellows

Azab is leading a project in collaboration with Virginia Tech and targeting the National Science Foundation Smart and Connected Communities Program. The proposal builds on a CCI-funded project and will address challenges in the civil infrastructure and environmental quality, learning environments, and workforce development domains. 

"This project is very special as we aim to seek funding to support a national-level cyber security-aware workforce development process for smart connected communities' critical infrastructure,” Azab said. 

“The recent attacks on mission-critical infrastructure applications, which are usually the base for any smart connected community, showed the desperate need for cybersecurity hands-on skill development. For that, we aim to employ our recent cutting-edge education and training tools like extended and virtual reality to build a training platform that supports remote and in-person interactions with a fully immersive representation of mission-critical infrastructure applications.

“The goal is to build on top of such a platform, (creating) a community of workforce developers, and a place where the workforce can seek help when needed. With the successful model that we built in our former CCI-sponsored grant, we noticed the value of having a pipeline of students and trainers where young students, trained by senior students, acquire advanced experience from their interaction with other senior students,” Azab said. 

“That level of continuous exchange of information and mentorship, when managed right, helps create a long-lasting community of educators and an experienced, aware workforce.”

Black os also Director of the Aerospace and Ocean Systems Laboratory of the Ted and Karyn Hume Center for National Security and Technology, Co-Director of the Center for Space Science and Engineering Research (Space@VT), and the Northrop Grumman Senior Faculty Fellow in C4ISR.  

Black is leading a proposal with Virginia Tech and Virginia Military Institute researchers to pursue National Science Foundation Engineering Research Center (ERC) funding to establish a Center for Secure Space Communications. The center will address emerging challenges related to the rapidly growing demand for more capable satellite network infrastructure. The need for such a center emerged recently; no existing ERC is situated in this area, Black noted. 

“CCI has a great model for student engagement, which really suits the research I do, and provides unique hands-on space and hands-on cyber experiences,” Black said. “These experiential research programs are also excellent tools for engaging industry, which we have leveraged on this program. Our vision is to propose extending this model to a federal center, which we will propose with the support of the CCI Fellow program.”

Davidson is well known for leading top projects, including the $3 million Virginia Cyber Navigator Program, which provides students with internships to work with Virginia election registrars to assess and improve the security of critical infrastructure used in elections.

In collaboration with Virginia Tech and Old Dominion University, Davidson is leading a proposal to the NSF Community Infrastructure in Computer and Information Science and Engineering (CIRC) program. The project’s objective is to create a multi-campus data collection, curation, and sharing infrastructure for use by the NSF Computer and Information Science and Engineering (CISE) community of cybersecurity and privacy researchers. 

A critical, novel, and distinguishing aspect of this infrastructure is that it provides the ability to carry out cyber-attack recreations within the operational networks. 

The infrastructure provides the ability to produce realistic, labeled (ground-truth) cybersecurity datasets. These datasets include network traffic collected at the gateways to the Internet backbone and various key locations within the enterprise networks. 

Further, end-point sensor data includes features such as process creation, memory usage, and more. The collected data provides realistic data sets with ground-truth labels to support cutting-edge, data-driven cybersecurity research.

“This federated infrastructure will be invaluable for developing new machine-learning algorithms for detecting zero-day attacks and large-scale attacks with complex kill chains,” Davidson said. 

We propose launching the Institute for the Mathematics of Technology-Inspired Applications (IMTIA) aims to be funded through the prestigious NSF Mathematical Sciences Research Institutes program described below. Positioned to serve as a national resource for the mathematical sciences and related communities, IMTIA will be a collaborative effort between Virginia Tech and the University of Virginia. It will be the first national institute dedicated to mathematics for science and engineering applications, driven by the capabilities and challenges of a digital world. Traditionally, mathematics has been inspired by the physical world, aiming to describe and explain natural phenomena. Today, unanswered questions also involve the digital realm, inspiring new mathematics that addresses those initial questions and can be expanded to develop novel theories with unexpected applications. IMTIA emphasizes mathematics at the forefront, advancing fields such as algebra, analysis, coding theory, cryptography, probability, scientific computing, mathematical physics, modeling, and dynamical systems—responses to, and drivers of, applications in wireless communications, artificial intelligence, quantum information theory, machine learning, security, algorithms, distributed computing, and data science. These themes are highly relevant to CCI, and IMTIA is expected to attract researchers of interest to CCI institutions, especially George Mason University, Virginia Commonwealth University, Virginia Tech, the University of Virginia, and William & Mary.

Virginia is uniquely situated, both geographically and intellectually, to host an MSRI, complementing NSF’s current portfolio, which is largely on the West Coast and in the Northeast. Placement in the National Capital Region affords Virginia a singular competitive advantage, capitalizing on the existing Virginia Tech footprint at the Innovation Campus to provide easy access to federal agencies, sponsors, and innovation partners.

Goodall is leading a proposal in collaboration with researchers from Old Dominion University and the College of William and Mary.

The vision for the National Science Foundation Engineering Research Center proposal is to direct smart cities technology to improve climate resilience in coastal communities. More frequent and intense storm events, combined with sea level rise and so-called “nuisance flooding” that can occur multiple times per year, are placing increased stress on coastal communities. The smart cities revolution playing out in cities across  the globe can bring needed technology to these coastal communities in their efforts to increase their resilience.  

“I have been working on coastal resilience for the past five-plus years and believe addressing the challenge will require new technologies and approaches developed through deep, convergent collaborations among computer scientists, engineers, planners, and others,” Goodall said. “A center-level grant from the National Science Foundation would provide support for a cross-institutional and cross-disciplinary team to make progress on this pressing societal challenge.” 

Traditional cybersecurity risk communication and office cybersecurity training focus on conveying scientific information related to the probability and consequences of the current cyber landscape. This communication and office training includes: (1) being aware of phishing emails, (2) not installing unauthorized software on company computers and devices, (3) identifying and reporting insider threats, and (4) not falling victim to ransomware and malware. We propose a paradigm-shifting approach to communicating cybersecurity risks and conducting office training related to cybersecurity threats.

Multiple studies have shown that scientific information alone rarely affects preparedness. This is especially true with respect to cybersecurity, as offices and businesses continue to increase digitalization and automation. It is further exacerbated by efforts to find the right trade-off between security and usability, which introduces new cybersecurity risks, especially when employees have varying levels of cyber awareness and technical expertise.

To address this need, we propose a framework that can be applied to any type of cyber threat to generate individualized cyber risk communication and/or office training containing desired stakeholder information. These messages and training change the traditional paradigm of cybersecurity risk communication because they are individualized using large language models (i.e., ChatGPT, BERT, Claude, Ernie, Falcon, Lambda) to be more inclusive of their audience and produce a more directed educational / training response. The result of this more inclusive, individual-focused material is an increased chance of positive interpretation and recipient action.

Secure communication in wireless networks is vital for protecting sensitive data, especially as reliance on wireless systems grows. Quantum methods, such as quantum key distribution, improve security but require specialized hardware, which limits the scalability and compactness of wireless devices. Topological devices offer a solution by leveraging the quantum properties of materials to provide inherent security at the physical layer in RF (radio frequency) communication. These devices enable scalable, energy-efficient, and secure wireless communication, making them ideal for embedded applications where traditional quantum setups are impractical.

We propose leveraging the unique quantum properties of topological insulators (TIs) to achieve highly secure wireless communication. TIs are distinctive quantum materials that exhibit spin-momentum locking of surface states, inherently linking the spin orientation of surface electrons with their direction of motion. When an RF current is injected into a TI sample, it generates a spin current with alternating spin polarization in nanomagnets deposited on the TI surface, exciting spin waves in the nanomagnets at the radio frequency of the injected current. These spin waves emit electromagnetic waves through the coupling of magnons and photons. The polarization of the main lobe in the radiation pattern can be adjusted by changing the direction of current injection with a multi-phase clock, allowing information to be encoded in the polarization, similar to quantum key distribution. This method provides secure data encoding that cannot be disrupted without physical access to the transmitting antenna. The antenna can be significantly miniaturized—by orders of magnitude smaller than the wavelength—and deeply embedded for concealment, making physical access extremely difficult and potentially impractical.

The U.S. leadership in wireless communications is critical to maintaining economic and national security, shaping the global evolution of mobile networks towards 6G.In support of this goal, there is a strong and growing interest in open and software-defined architectures for future wireless networks. For instance, the National Telecommunications and Information Administration (NTIA) is awarding $1.5 billion for accelerating the development, testing, and deployment of O-RAN (link).

Furthermore, the Office of the Under Secretary of Defense (OUSD) and the National Spectrum Consortium have recently launched an initiative to develop an open-source 5G/6G software stack. While of national interest, these efforts mainly focus on technologies operating in sub-6GHz bands. However, many of the disruptive innovations in wireless communications, sensing, resilience, and security occur in mid- and high-frequency spectrum bands, i.e., 7-15GHz and above 24GHz. The challenge is that software stacks and their orchestration solutions cannot be easily adapted for mid- and high-frequency spectrum bands, as they lack the capabilities to control phased antenna arrays and reflective surfaces needed to create and steer highly directional beams for coverage and service availability. To address this, this proposal aims to develop a new software radio platform that simplifies and accelerates experimental research in the mid- and high-frequency spectrum for future wireless networks and 6G.

This project aims to develop intelligent and secure agricultural technologies through a cyber-physical-social systems (CPSS) approach tailored for real-world farming environments. We propose a set of innovations that integrate artificial intelligence, solar-powered sensors, microrobotics, and edge-cloud collaboration to address key challenges in animal health, pest detection, and crop management. Our research focuses on energy-efficient, privacy-preserving, and adaptive AI systems that operate under resource-limited and dynamic farm conditions. The project will explore behavior-based animal disease detection, drone-coordinated strategies, microrobotic pest surveillance, and smart pest management systems powered by solar sensors.

This CCI Fellows award will boost competitive submissions to NSF CPS Frontiers, DoE ASCR, and NSF GCR programs. The effort combines expertise from Virginia Tech and Virginia State University and actively involves historically underrepresented communities in agriculture and technology. Our systems focus on resilience, scalability, and real-world deployment while supporting CCI’s mission in secure cyber-physical systems, autonomy, and data privacy. The project also promotes economic growth through the potential commercialization of intelligent sensing platforms and regional partnerships with Cooperative Extension networks. By advancing responsible AI and workforce training in cybersecurity and smart agriculture, this initiative aims to position Virginia as a leader in sustainable, secure, and inclusive agritech innovation.

The proposal aims to develop a first-of-its-kind research platform called Open-Milli-IoT for investigating and developing mmWave IoTs. Open-Milli-IoT aims at jointly orchestrating and managing mmWave (millimeter Wave) communication and IoT devices through programmable and intelligent radio networks in the form of Open Radio Access Networks (O-RAN).

"Overall, what inspired us to pursue this project is two critically important yet outstanding problems,” Pathak said. One, how can we create IoT devices that can provide very high data rates while still being extremely power efficient? Two, how can such devices be controlled and managed in a systematic manner through their integration in existing networks? 

“Chasing the solution to the first question drove us to create backscattering IoT devices at millimeter-wave frequencies, which are central to 5G and beyond wireless networks. 

“The use of O-RAN provides the necessary flexibility, security, and programmability for orchestrating these devices under one unified architecture. mmWave backscatter IoTs will be essential in various low-power, high-speed applications such as metaverse, logistics, safety, health care, etc., and their integration in 5G&B (5G & Beyond) (5G & Beyond) networks through O-RAN will ensure low-cost deployments and operations, and better adoption of the technology.”

Smart grids are vital to modern infrastructure, but their complexity and reliance on interconnected systems make them vulnerable to cyber threats. A common method to ensure security is to perform thorough system integrity checks on components and modules. However, these inspections are often tedious, require many resources, and are prone to human errors and targeted control mistakes. This research aims to automate system integrity checks within smart grids using AI-driven cybersecurity protocols. The goal is to create a self-monitoring and self-healing system that continuously maintains the integrity of smart grid operations by detecting and responding to anomalies in real-time to avoid disruptions. This AI-powered response system will be designed to adapt, recover, extend, and withstand malicious interactions with the grid. Often called "system resilience," achieving this property in real-world systems has proven challenging. An all-in-one AI-driven system that automates system integrity verification in smart grids would ensure all components operate within safe limits. This proposal addresses the current lack of such an automated system, though it faces challenges, especially in the optimal allocation of resources for continuous monitoring. Real-time response automation is a causal issue. To handle this, the aim is to develop an AI-based automated response mechanism that addresses integrity issues quickly, minimizing the time between detection and resolution. Resilience remains a complex and somewhat vague concept. Programming system properties that enable them to "adapt," "extend," "rebound," or demonstrate "robustness" is difficult to measure with standardized metrics.

This project will support coordination and proposal-writing efforts to develop a proposal for establishing a Center of Excellence in Artificial Intelligence (AI) Security and Safety at Old Dominion University (ODU). The proposed Center will bring together researchers from several ODU units and will enable new advancements in AI security, privacy, and safety by developing scientific foundations and technological breakthroughs needed to shape the ongoing AI revolution, along with practical, cross-cutting methods to provide adaptive capabilities for Hampton Roads, the Commonwealth of Virginia, and the nation.

Intelligent Ambient Computing in Dynamic Environments is aimed at the National Science Foundation’s Expeditions in Computing program. 

Similar to smartphones becoming integrated into our lives, ambient computing is expected to be commonplace, said Zhang, who also has joint appointments in the Department of Biomedical Engineering and the School of Data Science at UVA. “In this scenario, users will continually and subconsciously interact with their surroundings, and devices will respond to human actions automatically, collectively, continuously, and smartly.”

Zhang added, “to realize ambient computing that works as we envision, we need the next-generation of computing systems to make decisions and predictions dynamically under the constraints of evolving environments, shifting goals, limited resources, and security, privacy, and safety constraints. 

“Meanwhile, the unprecedented scale and complexity of machine learning models and the sensing, computing, and communications infrastructures require new joint cross-layer designs spanning all levels of computing, from algorithms to systems to hardware. We propose to address these challenges in a framework we call Intelligent Ambient Computing.”