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Author Information
Leilani Gilpin (UC Santa Cruz)
I'm an Assistant Professor in the Department of Computer Science and Engineering at UC Santa Cruz. My research focuses on the design and analysis of methods for autonomous systems to explain themselves. Before returning to academia, I worked at Sony AI on the GT Sophy Project. I received a Ph.D. in EEECS from MIT, an M.S. student in Computational and Mathematical Engineering at Stanford University, and a B.S. in Computer Science with Highest Honors, a B.S. in Mathematics with Honors, and a Music Minor at UC San Diego.
Julius Adebayo (MIT)
Julius Adebayo is a Ph.D. student at MIT working on developing and understanding approaches that seek to make machine learning-based systems reliable when deployed. More broadly, he is interested in rigorous approaches to help develop models that are robust to spurious associations, distribution shifts, and align with 'human' values. Website: https://juliusadebayo.com/
More from the Same Authors
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2021 : [IT4] Detecting model reliance on spurious signals is challenging for post hoc explanation approaches »
Julius Adebayo -
2021 : Speaker Introduction »
Leilani Gilpin -
2021 : Q/A Session »
Leilani Gilpin -
2021 : Speaker Introduction »
Leilani Gilpin -
2021 Workshop: eXplainable AI approaches for debugging and diagnosis »
Roberto Capobianco · Biagio La Rosa · Leilani Gilpin · Wen Sun · Alice Xiang · Alexander Feldman -
2020 Tutorial: (Track2) Explaining Machine Learning Predictions: State-of-the-art, Challenges, and Opportunities Q&A »
Himabindu Lakkaraju · Julius Adebayo · Sameer Singh -
2020 Tutorial: (Track2) Explaining Machine Learning Predictions: State-of-the-art, Challenges, and Opportunities »
Himabindu Lakkaraju · Julius Adebayo · Sameer Singh -
2018 : Posters 1 »
Wei Wei · Flavio Calmon · Travis Dick · Leilani Gilpin · Maroussia Lévesque · Malek Ben Salem · Michael Wang · Jack Fitzsimons · Dimitri Semenovich · Linda Gu · Nathaniel Fruchter