The five recipients are Dr. Waseem Abbas, assistant professor of systems engineering; Dr. Sourav Dutta, assistant professor of electrical and computer engineering; Dr. Kirill Lazebnik, assistant professor of mathematical sciences; Dr. Kyle McCall, assistant professor of materials science and engineering; and Dr. Xinda Wang, assistant professor of computer science. Four of the five, Abbas, Dutta, McCall and Wang, are members of the university’s Erik Jonsson School of Engineering and Computer Science, while Lazebnik belongs to the School of Natural Sciences and Mathematics. The portfolio of funded work illustrates how the CAREER mechanism can seed progress across the full stack of modern technology, from the atoms inside a transistor to the mathematical abstractions that describe dynamical behavior and the code that keeps the world’s software infrastructure safe.

University research leadership framed the awards as evidence of the institution’s growing strength in areas that will define the coming decades of technology. “From resilient networks and advanced semiconductors to artificial intelligence, cybersecurity and fundamental mathematics, these researchers are tackling complex challenges with the potential to shape the technologies and systems of the future,” said Dr. Joseph Pancrazio, vice president for research and innovation and professor of bioengineering. He emphasized that the awards also recognize the recipients’ commitment to integrating research and education, giving students the chance to learn through hands-on discovery and helping cultivate the next generation of researchers and innovators. That educational component is not incidental to the CAREER program; it is a core evaluation criterion, and each of the five UT Dallas projects embeds training, outreach or curriculum development alongside the technical work.

Dr. Waseem Abbas received a five-year award of $514,916 to confront one of the most consequential questions in networked engineering: what happens when a system designed to absorb disruption is hit by something worse. Robot teams, infrastructure networks and distributed computing systems, in which tasks are shared across many devices, are typically engineered with a certain tolerance for failure built in. If an attack, fault or environmental disturbance stays within that expected envelope, the system degrades gracefully. But when the disruption exceeds the threshold, performance can deteriorate rapidly and unpredictably, sometimes collapsing in ways that cascade through the entire network. Abbas aims to develop networked systems that adapt as conditions worsen, so that performance declines smoothly rather than failing catastrophically. A second strand of his research seeks to identify the most critical connections and components within a network, the nodes and links whose protection yields the greatest resilience. By concentrating defenses on those essential elements, operators could maintain core functions without paying for costly, blanket redundancy across every part of the system. The work has obvious implications for autonomous vehicle coordination, industrial automation and the distributed computing fabric that increasingly underpins everyday services.

Dr. Sourav Dutta’s award, totaling $501,234, targets the physical bottleneck that threatens to slow the artificial intelligence revolution: the semiconductor itself. As AI models and autonomous systems generate staggering volumes of data, conventional computer chips struggle to move information efficiently between the separate regions where data is stored, processed and transmitted. Every transfer across those internal distances costs energy and time, and at the scale of modern workloads the cost becomes prohibitive. Dutta will investigate ultrathin oxide semiconductor transistors with a property that could prove transformative: they can be manufactured at low temperatures and stacked vertically on top of conventional silicon electronics. Vertical stacking would shorten the distance data must travel, directly reducing energy consumption and potentially enabling faster, more efficient chips. Because the low-temperature fabrication process is compatible with existing silicon technology, the approach could be integrated with current manufacturing rather than requiring an entirely new industrial base. Dutta also plans to apply artificial intelligence and computational modeling to predict how candidate transistors will perform before they are built, accelerating design cycles and shrinking the optimization process that normally stretches across years of laboratory iteration.

On the software side of the engineering school, Dr. Xinda Wang received $617,397 to build AI tools that can help open-source software communities catch security vulnerabilities earlier, at the moment developers are making changes to code. Open-source software, assembled from publicly available code that anyone can inspect, contribute to or reuse, has become the invisible backbone of the digital world. It powers commercial products, government systems and critical infrastructure alike. That ubiquity carries a hidden risk: when a vulnerability exists in a widely used open-source component, it silently propagates into every downstream system that incorporates the original code, multiplying the potential blast radius of a single flaw. Wang’s team will train machine-learning systems to recognize patterns in how code changes are made and how those changes ripple through other parts of a software project, flagging suspicious modifications before they are merged and deployed. Just as importantly, the researchers will develop AI models capable of explaining why a particular change may pose a security risk. That explanatory capability matters because security teams and volunteer maintainers often operate with limited time and resources; a tool that simply raises an alarm without context is easily ignored, while one that articulates its reasoning can be trusted and acted upon.

The fourth engineering awardee, Dr. Kyle McCall, received the largest of the five grants, $796,646, to probe a question that sits at the frontier of materials science: how the local atomic structure of emerging semiconductor materials determines their properties and their potential in electronics and energy technologies. Many of the most promising new materials exhibit unusual behavior that arises from deviations of atoms away from their ideal, expected positions within the crystal lattice. These local structural distortions can dramatically alter how a material conducts, absorbs light or responds to electric fields, yet scientists do not fully understand how the deviations can be controlled through the composition and arrangement of the constituent atoms. Compounding the challenge, the distortions are invisible to conventional characterization techniques, which average over large regions and therefore miss the local disorder that matters most. McCall and his team will use total X-ray scattering, a technique sensitive to how atoms are locally bonded within a material, to map the relationship between chemical composition, atomic deviations and resulting properties. The ultimate goal is a set of design principles that researchers can use to create new semiconductor materials with desirable properties on demand. The project also carries an educational mission, providing undergraduates with hands-on research experience and developing educational resources for teachers and students across the Dallas-Fort Worth region.

The lone recipient in the School of Natural Sciences and Mathematics, Dr. Kirill Lazebnik, secured a $450,000 CAREER grant for work in pure mathematics with unusually broad applied reach. His research concerns rational functions, the mathematical objects formed as ratios of polynomials, which serve as fundamental tools for mathematicians, scientists and engineers who model and analyze complex systems. Rational functions appear throughout signal processing, dynamical systems and scientific computing, making advances in their theory potentially consequential far beyond mathematics departments. Lazebnik’s project aims to deepen understanding of the structure of the space of rational functions and to explore how these functions might be applied in additional areas of analysis and dynamics. Questions that sound abstract, such as how the space of such functions is organized and connected, often translate into practical insight for engineers studying stability, control and signal behavior. Like his colleagues, Lazebnik has built education into the heart of the grant, with undergraduate research opportunities and community outreach programs designed to train future mathematicians and widen access to the discipline.

Taken together, the five awards reveal a coherent picture of where foundational research investment is flowing and why. The problems the CAREER recipients have chosen sit precisely at the pressure points of contemporary technology: networks that must survive deliberate attack and random failure, chips that must move data without drowning in their own energy consumption, software supply chains that must be defended at the moment of change, materials whose properties are hidden in atomic-scale disorder, and mathematical structures that underpin our ability to model all of the above. Each project also treats education as an engineering problem in its own right, designing pipelines of trained students, teacher resources and community engagement that extend the impact of the research well beyond the laboratory. For UT Dallas, the sweep of the awards across two schools signals institutional momentum in fields where competition for federal support is fierce. For the researchers themselves, five years of stable funding at the start of an academic career is a rare luxury, the freedom to pursue ambitious, long-horizon questions, and to bring students along for the entire journey from first hypothesis to published result.

Subject of Research: 2026 NSF CAREER awards to five UT Dallas faculty supporting research on network resilience, oxide semiconductor transistors, open-source software security, atomic structure of semiconductor materials and rational functions.

Article Title: Technologies, math research get lift from CAREER awards

Article References: Technologies, math research get lift from CAREER awards. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: NSF CAREER awards, University of Texas at Dallas, network resilience, oxide semiconductor transistors, open-source software security, artificial intelligence, semiconductor materials, total X-ray scattering, rational functions, systems engineering, materials science, mathematical sciences

The two-day event, titled “POSE: Conference: A Community-Wide Convening to Grow Secure Open-Source Ecosystems in the Era of AI,” will bring together specialists from universities, technology companies, government agencies, nonprofit organizations, and open-source communities. Its central question is increasingly important as AI transforms software development: how can the global ecosystem of freely shared code remain trustworthy when machines are beginning to write, modify, test, and deploy software at unprecedented speed?

Open-source software forms the hidden foundation of much of the digital world. Operating systems, cloud platforms, web servers, databases, cybersecurity tools, scientific applications, and artificial-intelligence systems often depend on code maintained by distributed communities rather than a single corporation. A small library maintained by a handful of volunteers may be incorporated into thousands of commercial products and public services. This structure accelerates innovation, but it can also make vulnerabilities difficult to track, responsibilities unclear, and essential projects financially fragile.

The rapid emergence of AI-assisted programming is intensifying those pressures. Generative AI tools can produce large amounts of code in seconds, while autonomous or semi-autonomous AI agents may soon be able to select software components, write patches, run tests, and submit changes with limited human intervention. These capabilities could help developers repair vulnerabilities and maintain neglected projects, but they may also introduce errors at scale. A flawed suggestion generated once by an AI assistant could be copied into thousands of repositories, creating a vulnerability that spreads faster than conventional review processes can detect.

The conference will examine how open-source communities can respond to this changing technical environment without sacrificing the openness that makes them productive. Participants are expected to explore methods for improving code review, vulnerability disclosure, dependency management, automated testing, and software provenance. Provenance—the ability to determine where a piece of code came from, how it was modified, and which tools contributed to it—is becoming especially important as software increasingly combines human-written code with machine-generated components.

Security is only one part of the challenge. Open-source projects also depend on social and economic systems that are often overlooked. Many widely used packages rely on unpaid or underfunded maintainers who are responsible for responding to security reports, reviewing contributions, managing releases, and supporting users. When these maintainers are overwhelmed or leave a project, critical software can become vulnerable even if the underlying code was once carefully designed. The planned gathering will therefore address organizational and financial models that could make important projects more viable over the long term.

Legal and policy questions will also be part of the discussion. Open-source licenses determine how software can be copied, modified, and redistributed, but AI-generated code raises new questions about authorship, training data, attribution, and liability. Organizations may need clearer ways to document whether software was written by a person, generated by an AI system, or assembled from existing components. They must also determine who is responsible when an AI-assisted change introduces a security flaw into infrastructure used by millions of people.

Albanese, a professor and associate chair for research in Information Sciences and Technology and executive director of George Mason’s Institute for Digital Innovation, and Chen, a professor of computer science, will use facilitated plenary discussions, structured breakout sessions, and hands-on working activities to connect experts who rarely participate in the same conversations. The format is intended to move beyond broad statements about the importance of open source and toward practical recommendations that developers, institutions, policymakers, and funders can implement.

Expected outcomes include a synthesis of major themes, an assessment of gaps and opportunities, recommended next steps, and widely distributed materials to support future initiatives. The organizers hope the conference will help establish shared priorities across communities that often view the software ecosystem from different perspectives. A technology company may focus on supply-chain risk, a government agency on public resilience, a researcher on reproducibility, and a volunteer maintainer on the time required to review every change. Bringing these concerns together could produce more realistic security strategies.

The project is scheduled to begin in July 2026 and continue through late June 2027. Its importance extends beyond the conference itself because the software under discussion is embedded in everyday systems, from online services and medical technologies to transportation networks and scientific computing. As AI-generated code becomes commonplace, the strength of the digital infrastructure beneath society will depend not only on more powerful tools, but also on transparent development practices, durable communities, and sustained investment in the people who keep open-source software alive.

Subject of Research: Secure and sustainable open-source software ecosystems in the era of artificial intelligence.

Article Title: Albanese and Chen Receive Funding for Conference Aimed at Creating Growing Secure Open-Source Ecosystems in Era of AI

Web References: https://www.gmu.edu/about; https://www.gmu.edu/masonnow

Keywords

Artificial intelligence, open-source software, cybersecurity, software supply chain, AI-assisted development, AI agents, digital infrastructure, software security, George Mason University, National Science Foundation