MALVERN, PA — Penn State Great Valley is expanding research into artificial intelligence safety, medical applications and software accountability while integrating AI instruction into its graduate programs, positioning the Chester County campus to address growing demand for professionals who can develop and manage the technology responsibly.
The university’s research includes collaboration with the Linux Foundation’s Agentic AI Foundation on methods for evaluating and governing autonomous AI systems, alongside a separate project with Penn State College of Medicine examining computer vision technology for identifying early signs of Parkinson’s disease.
Youakim Badr, professor of data analytics and AI, is contributing to the development of evaluation methods and governance practices for AI agents, which can perform tasks and make decisions with varying degrees of autonomy.
The work focuses on establishing safeguards that maintain human oversight, improve system reliability and make automated decisions easier to explain and evaluate.
“AI systems are becoming more autonomous, but our methods for testing, certifying, monitoring and regulating them are still catching up. That creates risks,” Badr stated in a university report detailing the campus’s research and academic initiatives.
The effort reflects a broader research focus at Great Valley on AI accountability, including methods for monitoring automated decisions and identifying errors or unintended behavior.
Dusan Ramljak, assistant professor of software engineering, is studying whether blockchain technology can improve accountability by creating secure, transparent records of AI decisions.
Ramljak and his colleagues have published research in the Journal of Cybersecurity and Privacy and presented their findings at academic conferences.
Assistant Professor of AI Thao Minh Le is examining the social and legal implications of AI, including risks associated with misleading generated content and its potential effects on children’s learning and development.
The campus is also applying AI research to medical screening.
Badr and Le are collaborating with Joseph Seemiller, assistant professor of neurology at Penn State College of Medicine, to develop computer vision methods for analyzing movement abnormalities associated with Parkinson’s disease.
The researchers are investigating whether continuous analysis of patients’ joint movements can identify patterns that may be difficult to detect through conventional visual examinations.
“Computers can look at different joints all at the same time and can analyze movement continuously over time, and it’s a lot more efficient,” Le stated.
The research is intended to improve the identification of abnormal movement patterns that could indicate neurological disorders, potentially supporting earlier clinical assessment and intervention.
Alongside those projects, Great Valley is expanding graduate education in AI engineering, applied AI and business management.
The campus offers a Master of Artificial Intelligence degree with two pathways: AI engineering, focused on designing and deploying secure systems, and an online applied and generative AI option emphasizing organizational applications using low-code and no-code tools.
The degree is available through hybrid instruction or online through Penn State World Campus, with the applied and generative AI pathway offered exclusively online.
A new Master of Science in Artificial Intelligence provides a more research-intensive curriculum emphasizing programming, advanced AI methods and preparation for engineering or research careers.
Great Valley has also introduced an MBA in Artificial Intelligence, combining business management instruction with the technical knowledge needed to evaluate AI applications and manage organizational changes.
Existing MBA, data analytics and software engineering programs are being updated to incorporate AI literacy, responsible use, AI-assisted software development and automated planning.
The campus also offers AI micro-credential certificates for students with varying levels of programming experience.
Raghu Sangwan, director of Great Valley’s engineering programs, and Badr are leading efforts to connect technical instruction in programming, statistics and machine learning with training in system security, risk management and ethical deployment.
“The professionals who will thrive in the coming decade are those who can design the secure, scalable infrastructure that transforms AI from a hyped experiment into a foundational enterprise asset,” Sangwan stated.
Faculty members are also studying how AI affects software development and the reliability of computer-generated code.
Nathalia Nascimento, assistant professor of software engineering, requires students to complete selected assignments with and without AI assistance and evaluate the differences.
Everton Guimarães, associate professor of software engineering, is examining where AI tools improve development efficiency and where they introduce technical risks, particularly in complex software architecture.
Nascimento, Guimarães and their students have published research in journals including Empirical Software Engineering and the International Journal of Data Science and Analytics.
Their work also addresses the potential for AI systems to reproduce biases contained in training data, particularly when software is used to support decisions involving employment and other consequential matters.
Guimarães emphasized that fairness must be incorporated into software development through structured auditing and diverse perspectives rather than addressed only after systems are deployed.
Great Valley Chancellor and Dean Colin Neill is overseeing the broader integration of AI instruction across academic programs.
The university’s approach emphasizes using AI to extend employees’ capabilities rather than treating automated systems as direct substitutes for human judgment.
Badr described the distinction as central to evaluating the technology’s economic and organizational value.
“We should help society distinguish between AI hype and AI value by asking whether a technology improves human decisions, produces measurable benefits and earns the trust of the people who use it,” he stated.
Beyond AI governance and medical research, Great Valley faculty and students are applying the technology to aerospace systems, cybersecurity, regulatory compliance, medicinal chemistry, substance use disorder research and other fields.
The combined research and curriculum initiatives connect the campus’s graduate education programs with ongoing work on AI reliability, technical accountability and applications across industry and health care.
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