I'm a final-year Ph.D. candidate in the Computing and Mathematical Sciences department at Caltech. My advisor is Pietro Perona.

Research: My goal is to create algorithms that amplify the abilities of scientists, doctors, and other human experts. My work bridges the gap between traditional machine learning techniques and the challenges faced by human experts, including fine-grained categories, heterogeneous side information, and scarce/noisy/biased labels. I also use these real-world problems as the basis for new benchmark datasets, which measure algorithmic innovation in terms of progress on impactful applications. My work is supported in part by an NSF Graduate Research Fellowship and an Explorer Grant from the Resnick Sustainability Institute.

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).

I am on the 2022-2023 job market! Email is the best way to reach me.

Selected Publications

For a complete list, please see my Google Scholar page.

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 Data Video

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

Plain Academic