Scholar
Olivier J Hénaff
Google Scholar ID: Sx75CVsAAAAJ
Google DeepMind
Citations & Impact
Citations
4,694
H-index
19
i10-index
23
Publications
20
Co-authors
15
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Published multiple papers in top conferences such as NeurIPS, ICML, ECCV, ICCV; Participated in several projects including Active Data Curation Effectively Distills Large-Scale Multimodal Models, Context-Aware Multimodal Pretraining, etc.
Research Experience
- Currently a Senior Staff Research Scientist at Google DeepMind, researching self-supervised algorithms that extract structure from raw data, enabling data-efficient image recognition, behaviorally-relevant scene understanding, object discovery, and temporal correspondence. Recently, he has been interested in how visual representations might structure our memory, enabling flexible perceptual inference and long-video understanding.
Education
- PhD: Center for Neural Science at NYU, Advisor: Eero Simoncelli; Undergraduate: École Polytechnique and Lycée Sainte Geneviève, Major: Mathematics and Physics.
Background
- Research Interests: Understanding the principles underlying biological and artificial intelligence; Professional Field: Neural representation structure, self-supervised algorithms, visual system, etc.; Brief Introduction: In the face of changing environments, humans and animals produce complex behaviors with little to no supervision, which has led him to study the structure of neural representations in perceptual and physiological experiments.
Miscellany
- Has given talks at multiple international conferences, including the ECCV 2024 workshop, ICCV 2023 tutorial, University of Amsterdam's Deep Vision Seminar, etc.
