Five faculty members named AAAS Fellows

Five Virginia Tech faculty members have been named to the 2025 class of American Association for the Advancement of Science (AAAS) Fellows.

“Virginia Tech’s AAAS Fellows represent a distinguished community of scholars and innovators whose work spans disciplines from pioneering research and transformative teaching to technological advancement, leadership across sectors, and meaningful engagement with society,” said Dan Sui, senior vice president for research and innovation. “Their achievements reflect not only individual excellence, but also the strength of Virginia Tech’s collaborative, transdisciplinary research enterprise and its growing impact on the global stage.”

The following Virginia Tech faculty are among the nearly 500 scientists, engineers, and innovators who have been recognized for their scientific and socially distinguished achievements by one of the world’s largest general scientific societies and publisher of the Science family of journals.

Kevin Edgar, professor of biomaterials and associate dean of the Graduate School

AAAS citation: For pioneering contributions to the chemistry and engineering of polysaccharides, advancing fundamental understanding and innovative applications in biomaterials, drug delivery, and sustainable polymers, and for leadership in the profession.

A leader in sustainable materials research, Edgar’s work emphasizes understanding structure–property–performance relationships in renewable materials, enabling high-performance solutions that reduce reliance on petroleum-derived polymers. He has directed the the Institute for Critical Technology and Applied Science's Bio-Based Materials Center, was a founding co-director of the Infectious Disease Interdisciplinary Graduate Education Program, and is an editor-in-chief of the Carbohydrate Polymers journal. His research group designs and synthesizes derivatives of natural polysaccharides, otherwise known as long, complex chains of many simple sugar molecules linked together, to meet demanding performance requirements in applications such as drug delivery, tissue engineering, hydrogels, and biodegradable plastics.

William Hopkins, Thomas H. Jones Professor of Wildlife Conservation

AAAS citation: For distinguished contributions to the field of wildlife ecotoxicology, revealing effects of contaminants on amphibians and reptiles, and advancing science-based conservation strategies and environmental policy to protect biodiversity

A conservation physiology scholar, Hopkins conducts interdisciplinary research that links physiological mechanisms with ecological processes to understand how environmental stressors influence wildlife health and population dynamics. His work focuses on the effects of contaminants, habitat alteration, and climate change on amphibians, reptiles, birds, and bats, using innovative and minimally invasive approaches to assess sublethal impacts on survival, reproduction, and fitness. As director of the Global Change Center, Hopkins helps shape Virginia Tech’s research agenda in global change science and the environmental sciences. His research has informed conservation and regulatory decisions at state, national, and international levels, and he is widely recognized for translating complex scientific findings into actionable insights for policymakers and the public.

Chang Lu, Fred W. Bull Professor of Chemical Engineering 

AAAS citation: For distinguished contributions to the field of epigenomics — chemical modifications that regulate gene activity without altering DNA sequences— particularly for development of microfluidic epigenomic technologies and their application to neuroscience and cancer

Lu is a pioneer in applying microfluidic technologies to molecular and genome-wide biology, enabling faster and more cost-effective ways to map epigenomic changes and their roles in brain disorders ranging from seizures to addiction. A Fellow of the American Institute for Medical and Biological Engineering, Lu also developed a widely adopted electroporation technology, which is when an electrical pulse is used to create temporary pores in cell membranes through which payloads can pass, for efficient gene delivery in biomedical research. His work focuses on advancing biotechnologies to better understand and ultimately improve the diagnosis and treatment of cancer and neurological disorders.

Deborah Mayo, professor emerita of philosophy

AAAS citation: For contributions to the foundations of statistical inference, which engages both philosophers and statisticians and advances cross-cutting debates concerning evidence, inference, and scientific experiment.

Mayo brought international visibility to Virginia Tech through her scholarship in the philosophy of statistics, science, and principles of inference. She held a leadership position in the Philosophy of Science Association; she is an international fellow of the British Academy; and she was a visiting professor at the London School of Economics and Political Science for many years. Mayo has also written several books, including the award-winning “Error and the Growth of Experimental Knowledge,” and “Statistical Inference as Severe Testing.” She authored or coauthored more than 80 peer-reviewed articles, book chapters, and reviews. 

Daphne Yao, professor of computer science

AAAS citation: For contributions to enterprise data security and high-precision vulnerability screening.

Yao has pioneered state-of-the-art security solutions that use novel, highly effective artificial intelligence or mathematical algorithms to quickly and accurately find vulnerabilities, specifically designed to be easily implemented into existing operational systems to instantly enhance security. She was one of the first researchers to achieve deployment-grade accuracy for screening software and monitoring complex systems. Yao also conducted the world’s first measurement on payment card industry data security standards, providing in-depth and impactful insights to security compliance practice and regulation. In the health care domain, she led interdisciplinary teams with medical doctors to examine the trustworthiness of medical machine learning models.