Computer Science Faculty Members Named 2025 Sloan Research Fellows

Two faculty members in Carnegie Mellon University's School of Computer Science(opens in new window) will receive Sloan Research Fellowships(opens in new window) in 2025.

Zhihao Jia and Deepak Pathak are among the 126 early career researchers announced as fellows. More than a thousand researchers are nominated each year, and winners receive a two-year, $75,000 fellowship that can be used to advance their research.

"The Sloan Research Fellows represent the very best of early career science, embodying the creativity, ambition and rigor that drive discovery forward," said Adam F. Falk, president of the Alfred P. Sloan Foundation. "These extraordinary scholars are already making significant contributions, and we are confident they will shape the future of their fields in remarkable ways."

A prestigious award for young researchers, Sloan Research Fellowships recognize creativity, innovation and research accomplishments. Many past fellows have become distinguished figures in science.

Jia(opens in new window) is an assistant professor in the Computer Science Department(opens in new window), where he works on computer systems and compilers for machine learning. His current research focuses on building efficient, scalable and automated software systems for emerging machine learning applications, including large language models and generative AI tasks. He co-directs Catalyst(opens in new window), CMU's automated learning systems group, and is a member of the Parallel Data Lab(opens in new window). His work on optimizing machine learning parallelization and compilation is used by many companies and has impacted both academic and industry thinking about building such systems.

Pathak(opens in new window) is the Raj Reddy Assistant Professor in the Robotics Institute(opens in new window) with an affiliation in the Machine Learning Department(opens in new window). His research focuses on AI at the intersection of machine learning, robotics and computer vision, with the goal of building general-purpose foundation models for embodied physical intelligence. He aims to create agents that can continually develop knowledge and acquire new skills on their own, which often involves taking inspiration from learning in children and animals to build practical algorithms at the interface of machine learning and robotics. Pathak's group is known for several pioneering contributions to modern AI, including self-supervised learning, artificial curiosity algorithms and adaptive robot learning.