I am on the 2022-2023 job market! Email is the best way to reach me.
Research: I am a machine learning researcher specializing in deep learning and computer vision. I design algorithms for distilling valuable knowledge from real-world data, meaning large amounts of raw data with limited, noisy, and weak supervision. To enable this work, I collaborate with doctors, ecologists, and other domain experts to develop application-inspired benchmarks that test algorithms under realistic conditions and challenge traditional machine learning paradigms.
Previously: I graduated from Duke University in 2017 with a B.S.E. in Electrical and Computer Engineering and Mathematics. I've also spent time at Google Research, Microsoft Research, the Air Force Research Lab, the Duke University Marine Lab, and the Woods Hole Oceanographic Institution. I'm a proud product of public schools in Utah (Grantsville, Sandy, Salt Lake City), Nebraska (Omaha), and Texas (San Antonio).
My work is supported in part by an NSF Graduate Research Fellowship and an Explorer Grant from the Resnick Sustainability Institute.
Species Distribution Modeling for Machine Learning Practitioners: A Review
Sara Beery*, Elijah Cole*, Joseph Parker, Pietro Perona, Kevin Winner
ACM COMPASS 2021
Paper