| CARVIEW |
Julius Adebayo
I am cofounder of Guide Labs, where we are building
interpretable AI systems that humans and domain experts can easily audit, steer, and understand.
I got my PhD in Computer Science from MIT where I was
advised by
Hal Abelson, and supported
by Open Philanthropy.
In 2022-2023, I was a postdoctoral researcher at Prescient Design, where
I worked with Prof Kyunghyun Cho and Dr. Stephan Ra.
Before that, I was a brain resident at Google, and worked as a research engineer at Fast Forward Labs. Previously, I got a Masters degree in Computer Science and Technology Policy from MIT. I did my undergrad in Mechanical Engieering at BYU.
Selected papers
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(* equal contribution)
Aya Abdelsalam Ismail, Tuomas Oikarinen, Amy Wang, Julius Adebayo, Samuel Stanton, Taylor Joren, Joseph Kleinhenz, Allen Goodman, Hector Corrada Bravo, Kyunghyun Cho, Nathan C. Frey
ICLR 2025
Aya Abdelsalam Ismail*, Julius Adebayo*, Hector Corrada Bravo, Stephen Ra, Kyunghyun Cho
ICLR 2024
Fulton Wang*, Julius Adebayo*, Sarah Tan, Diego Garcia-Olano, Narine Kokhlikyan
NeurIPS 2023
Code
Julius Adebayo, Melissa Hall, Bowen Yu, Bobbie Chern
ICLR 2023
Julius Adebayo, Michael Muelly, Hal Abelson, Been Kim
ICLR 2022
Nishanth Arun, Nathan Gaw, Praveer Singh, Ken Chang, Mehak Aggarwal, Bryan Chen, Katharina Hoebel, Sharut Gupta, Mishka Gidwani, Julius Adebayo, Matthew Li, Jayashree Kalpathy-Cramer
Radiology: Artificial Intelligence, 3 (6): 2021.
Julius Adebayo, Michael Muelly, Ilaria Liccardi, Been Kim
NeurIPS 2020
Julius Adebayo, Justin Gilmer, Ian Goodfellow, Michael Muelly, Moritz Hardt, Been Kim
NeurIPS 2018
Pieter-jan Kindermans*, Sara Hooker*, Julius Adebayo, Maximilian Alber, Kristof Schutt, Sven Dahne, Dumitru Erhan, Been Kim
Explainable AI: Interpreting, Explaining, and Visualizing Deep Learning, 2018
Mikella Hurley and Julius Adebayo
Yale Journal of Law and Technology, 2017
Julius Adebayo and Lalana Kagal
Fairness, Accountability, and Transparency in Machine Learning (FAT/ML) Workshop, 2016