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.

Selected Publications

See Google Scholar for a complete list.

ECCV

On Label Granularity and Object Localization
Elijah Cole, Kimberly Wilber, Grant Van Horn, Xuan Yang, Marco Fornoni, Pietro Perona, Serge Belongie, Andrew Howard, Oisin Mac Aodha
ECCV 2022
Paper Website

CVPR

When Does Contrastive Visual Representation Learning Work?
Elijah Cole, Xuan Yang, Kimberly Wilber, Oisin Mac Aodha, Serge Belongie
CVPR 2022
Paper Website

CVPR

Multi-Label Learning from Single Positive Labels
Elijah Cole, Oisin Mac Aodha, Titouan Lorieul, Pietro Perona, Dan Morris, Nebojsa Jojic
CVPR 2021
Paper Code Video

CVPR

Benchmarking Representation Learning for Natural World Image Collections
Grant Van Horn, Elijah Cole, Sara Beery, Kimberly Wilber, Serge Belongie, Oisin Mac Aodha
CVPR 2021 (Oral)
Paper Code+Data Video

COMPASS

Species Distribution Modeling for Machine Learning Practitioners: A Review
Sara Beery*, Elijah Cole*, Joseph Parker, Pietro Perona, Kevin Winner
ACM COMPASS 2021
Paper

ICCV

Presence-Only Geographical Priors for Fine-Grained Image Classification
Oisin Mac Aodha, Elijah Cole, Pietro Perona
ICCV 2019
Paper Code Video

Based on Plain Academic