CICS’s Yuriy Brun Named an IEEE Fellow

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Yuriy Brun, professor in the Manning College of Information and Computer Sciences (CICS), has been named a fellow by the Institute of Electrical and Electronics Engineers (IEEE), the world’s largest technical professional organization dedicated to advancing technology for the benefit of humanity.

Brun is part of the 2025 class of 338 new fellows representing 58 universities, companies and research centers from around the world. The IEEE Fellow recognition is the organization’s highest member grade, with less than 0.1% of voting IEEE members elevated to fellows annually.

Brun, who joins five current and seven emeriti CICS faculty members who are IEEE Fellows, was cited by the IEEE for his “contributions to software bias mitigation and to software engineering automation.” His work focuses on increasing the trustworthiness of software by developing techniques that make software less buggy and less biased. Brun is recognized for his efforts to simplify the development and deployment of software systems and ensuring they align with societal needs for fairness.

Brun credited his collaborators and UMass Amherst support for his success.

“I’m grateful to be working with fantastic students and colleagues who push tirelessly beyond the state of the art to generate scientific knowledge and help engineers build software we can all trust,” Brun said. “Working in a college that encourages and rewards collaboration helps us enact real-world impact, and our atmosphere that focuses on teamwork makes creating top-quality science possible.”

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A notable way in which modern software has lost users’ trust is by exhibiting racist or sexist behavior, often because of learning from biased data. Brun’s well-known contributions to preventing and correcting bias in machine learning include his 2017 paper, co-authored with CICS Professor Alexandra Meliou, “Fairness Testing: Testing Software for Discrimination,” which won an ACM SIGSOFT Distinguished Paper Award that year.

The paper, which has been cited over 400 times, came at a time when software fairness was not a common consideration in the development lifecycle and introduced some of the first techniques that automatically test software for bias. Since then, companies such as IBM, Microsoft and Google have introduced tools to detect and mitigate bias in machine learning software. 

In addition, Brun, Associate Professor Philip Thomas, and other colleagues from UMass Amherst and Stanford University developed a framework that fundamentally re-envisions machine learning to produce trustworthy models guaranteed to be safe and fair.

“The positive response this research has received shows that people care about using artificial intelligence and machine learning responsibly,” Brun said. “That means ensuring that we learn to build systems that will not discriminate and that will not exacerbate biases from the data.”

“Yuriy’s focus on fair and accurate results in computing exemplifies our college’s ethos of computing for the common good,” said Donna M. and Robert J. Manning Dean of CICS Laura Haas. “His commitment to collaborative and multidisciplinary research has made an important impact in the field of computing.”

Brun’s current work further builds toward his vision for engineering “software you can trust,” moving from automated testing and repair of software systems to automatically proving that software is correct. Toward that goal, Brun applies artificial intelligence to formal verification, automating that critical piece of making software systems more trustworthy.

Brun joined the CICS faculty in 2012. Previously, he was a postdoctoral fellow at the University of Washington. He received his master’s and doctorate in computer science from the University of Southern California in 2006 and 2008, respectively, and his master’s in engineering along with a double bachelor’s in computer science and engineering and in mathematics from the Massachusetts Institute of Technology in 2003.

More information on Brun’s work is available on the CICS News website and more information about the IEEE Fellow program can be found on the IEEE website.