Hannah Choi Named A Sloan Fellow

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Hannah Choi of the School of Mathematics has joined the ranks of Georgia Tech early career scientists selected to receive prestigious Sloan Research Fellowships.

Choi and Henry S. “Pete” La Pierre of the School of Chemistry and Biochemistry are among 118 early career researchers across the United States and Canada named as 2022 Sloan Fellows

"Today's Sloan Research Fellows represent the scientific leaders of tomorrow," says Adam F. Falk, president of the Alfred P. Sloan Foundation. "As formidable young scholars, they are already shaping the research agenda within their respective fields — and their trailblazing won't end here."

Sloan Research Fellowships are some of the most competitive and prestigious awards available to early career researchers. They are also often seen as a marker of the quality of an institution’s science faculty — and proof of an institution’s success in attracting the most promising junior researchers to its ranks. Since the first Fellowships were awarded in 1955, nearly 50 faculty from Georgia Institute of Technology have received the honor.

“I am extremely excited and honored to be named a Sloan Fellow,” Choi says. “I am deeply grateful to my research group members, mentors, colleagues and collaborators who made this possible, and I appreciate support from the School of Mathematics and the College of Sciences very much.”

Choi plans to use the grant to expand on current research projects on biological neural networks. “Specifically, with this grant, I hope to investigate computational roles of network complexities manifested by diverse neural dynamics and intricate connectivity among different types of neurons, in data-driven, functional neural networks across multiple scales, modalities, and systems. This study, therefore, will help us better understand how robust and efficient computation emerges from the unique complexity of biological neural networks, which then can be applied to innovate neuromorphic computing.”

The Choi Research Group in Mathematical Neuroscience’s primary goal “is to understand how efficient and adaptable neural coding emerges from complex connectivity structure and rich neural dynamics in both biological and artificial neural networks at multiple scales.”

Several current and former College of Sciences researchers — along with a number of College of Engineering faculty — are also recent recipients of Sloan Fellowships:



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