Xi Lu selected as AI Research Fellow by Computing Research Association

BUFFALO, N.Y. – Xi Lu, PhD, assistant professor of information science in the Graduate School of Education at the University at Buffalo, has been selected as a 2026-2027 CRA Trustworthy AI Research Fellow.

Funded by Microsoft, the fellowship is a program of the Computing Research Association (CRA) that supports early-career computing researchers. The researchers perform interdisciplinary training in the social sciences to integrate ethical, societal and human-centered considerations into the development of artificial intelligence (AI).

Lu, who has a joint appointment with the Department of Computer Science and Engineering in the School of Engineering and Applied Sciences, is one of eight fellows selected this year from a pool of more than 300 applicants.

“This year’s fellows are tackling some of the hardest questions in AI — not just how to build these systems, but how to ensure they serve people well,” says Mary L. Gray, principal investigator of Project Resolve, MacArthur Fellow and chair of the CRA Trustworthy AI Research Fellowship Advisory Committee. “They’re bringing together technical excellence with insights from the social sciences, law, design and community partnerships in ways that will be fundamental to the future of trustworthy AI.”

Lu, who joined UB in 2024, investigates how sociocultural contexts shape people’s experiences with health technologies.

“I am incredibly honored and excited to be selected as part of the inaugural CRA Trustworthy AI Research Fellowship cohort, especially at this early stage of my career,” Lu says. “One aspect I am looking forward to most is connecting with other early-career faculty and researchers who share an interest in trustworthy AI.”

Through the fellowship, Xi says she will deepen her community-engaged research on women’s health and culturally responsive pregnancy technologies — work that earned a CHI 2025 Best Paper Award and centers the lived experiences of underserved communities in the design of health AI systems.

Over the next year, fellows will engage in intensive interdisciplinary training and sustained peer collaboration. The fellowship includes a four-day, in-person field school on July 26-31 in Cambridge, Mass.

“Beyond the field school, I also plan to use the fellowship to participate in relevant workshops, conferences and collaborative activities throughout the year,” Lu says. “These opportunities will help me integrate perspectives from computing, ethics, policy and the social sciences into my research, and ultimately design AI systems that better serve underserved communities.”