UW News

February 27, 2019

Three UW scientists awarded Sloan Fellowships for early-career research

UW News

Three faculty members at the University of Washington have been awarded early-career fellowships from the Alfred P. Sloan Foundation. The new Sloan Fellows, announced Feb. 19, include Kelley Harris, an assistant professor of genome sciences at the UW School of Medicine; and Alvin Cheung and Shayan Oveis Gharan, both assistant professors in  the Paul G. Allen School of Computer Science & Engineering.

Open to scholars in eight scientific and technical fields — chemistry, computer science, economics, mathematics, molecular biology, neuroscience, ocean sciences and physics — the fellowships honor those early-career researchers whose achievements mark them among the next generation of scientific leaders.

The 126  Sloan Fellows for 2019 were selected in close coordination with the research community. Candidates are nominated by their peers, and fellows are selected by independent panels of senior scholars based on each candidate’s research accomplishments, creativity and potential to become a leader in his or her field. Each fellow will receive $70,000 to apply toward research endeavors.

This year’s fellows come from 57 institutions across the United States and Canada, spanning fields from evolutionary biology to data science.

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Kelley Harris

Harris is studying the recent evolutionary history of humans and other species through the lens of population genetic theory and advances in DNA sequence analysis. Among her several research topics is the fitness cost of Neanderthal and ancient human interbreeding. She is looking at how Neanderthals’ unhealthy inbred gene pool may have limited their contribution to modern genetic diversity. The findings might offer a broader lesson for conservational biology on attempting genetic rescue of inbred species.

Harris also has undertaken genomic studies of ancient human migration patterns across Earth, such as the peopling of the Americas.

“A major focus of our group is studying subtle differences between closely related populations,” said Harris.

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Alvin Cheung

Cheung engages in cross-disciplinary research as a member of the Allen School’s Database and Programming Languages & Software Engineering groups. In his young career, Cheung has produced multiple, paradigm-shifting solutions spanning data management, data analysis and end-user programming.

“From booking plane tickets to browsing social networking websites, we interact with large amounts of data every day,” said Cheung. “My group works on new techniques to help users process and manage data easily, with the goal to simplify software developers’ efforts to build databases and applications without compromising on performance, and enable the rapid development of database applications that provide efficient and reliable data access to all.”

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Shayan Oveis Gharan

Oveis Gharan is a member of the Allen School’s Theory of Computation group. He focuses on the design and analysis of efficient algorithms for solving fundamental NP-hard counting and optimization problems at the heart of the theory and practice of computing. These problems have implications over a wide range of fields, from logistics and marketing to planning and policy-making, all of which cry out for new and better computational tools for managing and exploiting the vast quantities of data available.

“I encode a discrete phenomenon in a complex multivariate polynomial, and I understand it via the interplay of the coefficients, zeros, and function values of this polynomial,” said Oveis Gharan. “Although these polynomials are so large that they cannot be stored in all computers in the world combined, I use their analytical properties to design efficient optimization algorithms for the underlying discrete phenomenon.”

Among Oveis Gharan’s most notable contributions to date are his works on the Traveling Salesman Problem, or TSP, and its asymmetric variant — one of the most studied problems in optimization — and his very recent work on counting problems related to matroids. Oveis Gharan and his collaborators studied the TSP using analytical techniques, proposing a new class of algorithms for variants of the TSP and introducing novel analysis of classical algorithms for this problem dating back 50 years. The team’s efforts produced the first improvement on existing approximation algorithms, which broke barriers that had stood for three decades despite substantial previous attempts within the theoretical computer science community.

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For more information, contact Jackson Holtz at jjholtz@uw.edu.

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