Alfred P. Sloan Foundation has awarded Sloan Research Fellowships to two computer engineers from the University of Michigan's College of Engineering: Thatchaphol Saranurak and Andrew Owens.
They are among 126 early-career researchers selected from institutions in the United States and Canada because their creativity, innovation and research accomplishments distinguish them as the next generation of leaders. Sloan Research Fellowships are one of the most competitive and prestigious awards available to early-career scholars, and they are seen as evidence of an institution's success in attracting the most promising early-career researchers to its ranks.
Sloan fellows receive a two-year, $75,000 prize that can be used to advance their research. They must hold a doctorate or equivalent degree in chemistry, computer science, earth system science, economics, mathematics, neuroscience, physics or related fields.
Saranurak, the Morris Wellman Faculty Development Assistant Professor of Computer Science and Engineering, develops algorithms that more efficiently compute graph networks of systems that change over time, such as social networks, traffic systems and the internet.
Conventional algorithms often need to recalculate an entire network to incorporate new information, but Saranurak's new algorithms allow networks to adapt to new information without recomputing everything from scratch. His methods could benefit any system that can be described as a graph network. For example, emergency responders could determine the fastest route through a city damaged by a natural disaster more quickly.
"I feel truly honored to receive the Sloan Research Fellowship," Saranurak said. "This recognition is both exciting and motivating, and I look forward to making more progress in algorithm design in the future. I feel grateful and lucky for all the support I have received from my mentors, students, and colleagues."
Owens' work has focused on developing machine perception systems that can learn from multisensory data that hasn't been labeled by humans. His research focuses on the use of synchronized audio and video, sometimes including tactile signals.
These foundations have many applications such as predicting sound from silent videos, applying speech methods to puppets and cartoons, reconstructing the relative positions of objects and the camera with audio data, tracking objects, and improving robot grasping by combining visual and tactile signals. Owens has also developed methods for detecting fake and manipulated images.
"I'm incredibly grateful to be receiving this award, which will support my research group's efforts to create computer vision systems that require less supervision from human teachers," Owens said.
U-M faculty have received 183 Sloan Research Fellowships since the first were awarded in 1955.