Katie Collins Named as 2020-21 Goldwater Scholar

Katie Collins running at the NEWMAC Cross Country Championship.

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Cambridge, Mass. (April 13) -- MIT cross country/track and field junior Katie Collins (Newton, Mass.) is one of three MIT students who has been chosen as a 2020-21 Goldwater Scholar. Over 5,000 college students from across the United States were nominated for the scholarships, from which only 396 recipients were selected based on academic merit.

Katie Collins Cross Country Bio
Katie Collins Track and Field Bio

A third-year majoring in brain and cognitive sciences with minors in computer science and biomedical engineering, Collins got involved with research in high school, when she worked on computational models of metabolic networks and synthetic gene networks in the lab of Department of Electrical Engineering and Computer Science Professor Timothy Lu at MIT. It was this project that led her to realize how challenging it is to model and analyze complex biological networks. She also learned that machine learning can provide a path for exploring these networks and understanding human diseases. This realization has coursed a scientific path for Collins that is equally steeped in computer science and human biology.

Collins, who was a USTFCCCA All-American in cross country, finished 15th at the 2019 NCAA National Championship and was also a 2020 Indoor NCAA qualifier in both the 3,000 and 5,000 meters. In cross country, Collins is a three-time All-Region performer, a three-time NEWMAC All-Conference selection and a two-time Academic All-Conference honoree. She is also a former New England D3 Outdoor Champion in the 5,000 meters, a four-time All-New England D3 selection and three-time NCAA track and field qualifier.

Over the past few years, Collins has become increasingly interested in the human brain, particularly what machine learning can learn from human common-sense reasoning and the way brains process sparse, noisy data. "I aim to develop novel computational algorithms to analyze complex, high-dimensional data in biomedicine, as well as advance modelling paradigms to improve our understanding of human cognition," explains Collins. In his letter of recommendation, Professor Tomaso Poggio, the Eugene McDermott Professor in the Department of Brain and Cognitive Sciences and one of Collins' mentors, wrote, "It is very difficult to imagine a better candidate for the Goldwater fellowship." Collins plans to pursue a PhD studying machine learning or computational neuroscience and to one day run her own lab. "I hope to become a professor, leading a research program at the interface of computer science and cognitive neuroscience."

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