image: Jing Yang, associate professor of electrical and computer engineering at the University of Virginia
Credit: Matt Cosner, University of Virginia School of Engineering and Applied Science
Jing Yang, an associate professor of electrical and computer engineering at the University of Virginia, has been named an IEEE Fellow, the highest honor bestowed by the Institute of Electrical and Electronics Engineers.
As few as 0.1% of IEEE’s voting members receive the honor annually. “The grade of Fellow recognizes unusual distinction in the profession and is reserved for a person with an outstanding record of accomplishments in any of the IEEE fields of interest,” the organization wrote in its announcement.
“The accomplishments that are being honored have contributed importantly to the advancement or application of engineering, science and technology, bringing the realization of significant value to society at large.”
Yang was recognized for her pioneering research on energy-harvesting wireless communications and her contributions to “Age of Information” optimization. The former enables devices in places with limited power and connectivity by harvesting energy from environmental sources, such as the sun, vibrations or radio waves. The latter refers to how current information is when a computational decision is made — a critical factor for applications such as patient monitoring, autonomous vehicles and power-grid operations.
For Yang, whose career has been dotted with awards, this one is particularly meaningful. “I felt incredibly blessed and grateful to receive this recognition, and I’m deeply thankful for the mentors, colleagues and students who made it possible,” she said.
“This honor marks an important milestone in my career, as it reflects my work on areas that aim to improve efficiency, timeliness and sustainability in modern wireless networks.”
Yang’s department chair, American Telephone and Telegraph Company Professor of Engineering Scott Acton, said Yang’s influence more than warrants the recognition.
“Jing has helped reimagine wireless systems,” Acton said. “What she has done for energy-harvesting communications and information timeliness means the rest of us benefit from smarter technologies that are safer, more reliable and less expensive. And I believe that her recent work in the reinforcement learning area of AI will be of equal or greater impact.”
Yang’s chief nominator, IEEE Fellow Jingxian Wu, called her a trailblazer whose research has inspired new directions in the field, generated numerous publications and earned more than 6,900 Google Scholar citations.
“Over the past 15 years, she has pioneered energy harvesting communications and significantly advanced the study of Age of Information,” wrote Wu, who mentored Yang when she taught at the University of Arkansas, where he is a professor.
Wu noted that Yang was the first to design optimal transmission policies for energy-harvesting wireless systems and among the earliest researchers to recognize a paradigm shift in the field. She proposed a new energy-management framework that helped launch an area of study known as Simultaneous Wireless Information and Power Transfer, or SWIFT. The topic has since become widely explored in energy-harvesting communications.
Yang also broke new ground by addressing how unpredictable energy availability affects information freshness in self-powered sensor networks. She introduced tools and frameworks that broadened the scope of Age of Information research.
Her work has continued to shape the field by linking Age of Information with other fundamental information-theoretic metrics, Wu added. “Establishing such connections is crucial for leveraging AoI in diverse real-world applications, enabling more effective and interdisciplinary solutions to complex challenges.”
Yang received the National Science Foundation CAREER award in 2015 and the IEEE Women in Communications Engineering Early Achievement Award in 2020, and was selected as one of the 2020 N2Women: Stars in Computer Networking and Communications.
She served as an editor for IEEE Transactions on Wireless Communications from 2020 to 2025 and for IEEE Transactions on Green Communications and Networking from 2017 to 2020. She is now an area editor for IEEE Transactions on Green Communications and Networking and an associate editor for IEEE Transactions on Information Theory and for IEEE Transactions on Cognitive Communications and Networking.
While her early research focused on wireless communications and networking, it quickly expanded to incorporate artificial intelligence and machine learning.
“AI and machine learning are powerful tools that are transforming nearly every sector of society,” said Yang, who holds a courtesy appointment in the Department of Computer Science in UVA’s School of Engineering and Applied Science.
“My research aims to improve their efficiency, transparency, trustworthiness and reliability, so that these technologies can be used more safely and effectively in everyday life.”