Key Takeaways
- The University at Buffalo (UB) is leading two NSF‑funded projects totaling $950,000 aimed at training the next‑generation U.S. workforce in artificial intelligence (AI), cybersecurity, and advanced manufacturing.
- Wenyao Xu, PhD, Carl V. Granger Endowed Chair Professor in UB’s Department of Computer Science and Engineering, serves as principal investigator on both awards, leveraging UB’s longstanding expertise in AI and biometrics.
- The first award ($450,000) is a Research Experiences for Undergraduates (REU) site grant that will provide intensive summer research training in cybersecurity and AI to 30 undergraduate students (10 per year) recruited nationwide, with a focus on under‑represented and first‑generation college students.
- Projects in the REU program explore frontier technologies in authentication and biometrics, including micro‑expression recognition, 3D finger‑vein imaging, ECG‑based continuous authentication, and cancelable biometric systems derived from brainwave signals.
- The second award ($500,000) is a CyberTraining grant that launches a joint UB–University of Georgia (UGA) program on “Secure Agentic AI for Advanced Manufacturing,” training 54 graduate and undergraduate students via an eight‑module curriculum and a hands‑on cyber‑physical testbed.
- This program teaches students to design, deploy, and govern AI agents that combine large language models, vision‑language models, and edge robotics while incorporating safeguards such as physics‑informed machine learning to ensure trustworthy autonomous systems.
- Both initiatives emphasize building a national pipeline of skilled talent capable of creating AI systems that are powerful, secure, and trustworthy—critical needs for the nation’s cybersecurity, AI, and advanced manufacturing sectors.
- The awards reinforce UB’s role as a hub for workforce development, extending its impact through collaboration with UGA and reinforcing a decade‑long partnership between the research teams.
- By integrating research experience with practical, security‑focused training, the projects aim to produce graduates who can immediately contribute to industry and government efforts safeguarding critical infrastructure and advancing smart manufacturing.
Overview of the NSF‑Funded Workforce Training Initiative
The University at Buffalo has secured two complementary National Science Foundation awards that together amount to $950,000 over three years. These grants are designed to strengthen the nation’s talent pool in three strategically important domains: artificial intelligence, cybersecurity, and advanced manufacturing. By anchoring the effort in UB’s Department of Computer Science and Engineering and drawing on interdisciplinary expertise across the university, the initiative seeks to create a sustainable pipeline of skilled professionals who can develop AI‑driven solutions that are both innovative and secure.
Leadership and Collaborative Structure
Wenyao Xu, PhD, the Carl V. Granger Endowed Chair Professor in UB’s Department of Computer Science and Engineering, serves as the principal investigator on both awards. His leadership brings together a team of co‑principal investigators and collaborators whose combined expertise spans biometrics, biomedical engineering, industrial systems, and advanced manufacturing. Jun Xia, PhD, a professor in the Department of Biomedical Engineering, acts as co‑PI for the REU site, while Chi Zhou, PhD, professor in UB’s Department of Industrial and Systems Engineering, co‑leads the CyberTraining grant. The partnership also includes Hongyue Sun, PhD, an associate professor in the Department of Mechanical Engineering at the University of Georgia, who contributes essential knowledge in intelligent systems and manufacturing processes. This multi‑institutional collaboration reflects a decade‑long working relationship that has already yielded joint publications, grant successes, and shared research infrastructure.
Undergraduate Research Experience in Cybersecurity and AI
The first award, a $450,000 Research Experiences for Undergraduates (REU) site grant approved by the NSF in May, will host an intensive summer research program focused on “Frontier Technologies in Authentication and Biometrics.” Over three years, the program will admit 30 undergraduate students—10 each year—recruited from across the United States, with deliberate outreach to first‑generation college students, those from economically disadvantaged backgrounds, and learners at institutions with limited research resources. Participants will engage in hands‑on projects that apply AI techniques to real‑world security challenges, such as micro‑expression recognition for deception detection, 3D finger‑vein imaging for touchless authentication, electrocardiogram‑based continuous authentication systems, and cancelable biometric schemes generated from brainwave signals. By working on these cutting‑edge topics, students gain practical experience in both AI algorithm development and cybersecurity evaluation, preparing them for graduate study or immediate entry into the workforce.
Emphasis on Broad Participation and Impact
A hallmark of the REU initiative is its commitment to diversity and inclusion. The program actively recruits students who traditionally have been underrepresented in STEM fields, providing them with mentorship, stipends, travel support, and access to UB’s state‑of‑the‑art laboratories. By lowering barriers to entry, the grant aims to democratize access to high‑quality research experiences, thereby enriching the perspectives that shape future AI and cybersecurity innovations. Moreover, the renewal of this REU site—marking its second consecutive NSF award—underscores the agency’s confidence in UB’s ability to deliver impactful, high‑quality training that aligns with national priorities.
Secure Agentic AI for Advanced Manufacturing
The second award, a $500,000 NSF CyberTraining grant approved in October 2025, launches a joint UB–University of Georgia program titled “Secure Agentic AI for Advanced Manufacturing.” This effort builds on a previously completed UB CyberTraining program that focused on cybersecurity for manufacturing environments. The new initiative expands the scope to encompass the design, deployment, and governance of AI agents—autonomous software entities that perceive, reason, and act within cyber‑physical systems. Students will learn to integrate large language models (LLMs), vision‑language models (VLMs), and edge robotics while embedding safeguards such as physics‑informed machine learning to ensure that autonomous operations remain trustworthy, safe, and compliant with operational constraints.
Curriculum Structure and Hands‑On Testbed
The training comprises an eight‑module curriculum that blends theoretical foundations with practical laboratory work. Modules cover topics including AI fundamentals for manufacturing, sensor fusion and perception, reinforcement learning for control, security threats to agentic systems, privacy‑preserving techniques, robustness verification, ethics and policy, and systems integration. Throughout the program, participants will access a shared cyber‑physical testbed that replicates realistic factory floor scenarios, enabling them to experiment with AI‑driven robotic arms, conveyor systems, and quality‑inspection stations under controlled conditions. By confronting realistic security challenges—such as adversarial attacks on perception models or manipulation of control commands—students develop the skills needed to harden AI agents against both cyber and physical threats.
Collaborative Expertise and Long‑Term Partnership
The UB–UGA team brings together a decade of collaborative research, which has produced joint publications, shared datasets, and complementary strengths in AI, cybersecurity, and advanced manufacturing. Wenyao Xu’s expertise in AI and biometrics informs the perception and authentication components of the agentic systems. Chi Zhou’s background in industrial systems engineering ensures that the training aligns with manufacturing workflows, safety standards, and production metrics. Hongyue Sun’s work in intelligent systems and mechanical engineering at UGA contributes deep knowledge of robotics, dynamics, and control theory, essential for building reliable edge‑robotic platforms. This synergy allows the program to address both the software and hardware dimensions of secure agentic AI, producing graduates who can bridge the gap between algorithmic innovation and real‑world implementation.
Vision for a National Workforce Pipeline
Reflecting on the dual awards, Wenyao Xu emphasized that the initiatives are fundamentally about people as much as technology. By providing students across the country with immersive, security‑focused research experiences, the projects aim to cultivate a workforce capable of building AI systems that are not only powerful but also resilient, trustworthy, and aligned with societal needs. The ultimate goal is to meet the growing demand for professionals who can safeguard critical infrastructure, advance smart manufacturing, and drive responsible AI innovation. UB’s leadership in these efforts, bolstered by strategic partnerships with UGA and a clear commitment to inclusive recruitment, positions the university as a national hub for developing the talent that will shape the future of AI, cybersecurity, and advanced manufacturing for years to come.