Scholar
Fartash Faghri
Google Scholar ID: KUG_tG0AAAAJ
Apple ML Research
Citations & Impact
Citations
3,791
H-index
16
i10-index
20
Publications
20
Co-authors
17
list available
Publications
Resume (English only)
Academic Achievements
- MobileCLIP2 received J2C Certification and will be presented at ICLR 2026; MobileCLIP2 models and associated code have been released; MobileCLIP2 was accepted by TMLR with Featured Certification; delivered a keynote at ICML 2025 TTODLer-FM workshop; CCFM is officially a NeurIPS 2025 workshop; TiC-LM will be an Oral presentation (Top 8%) at ACL 2025; FastVLM will be presented at CVPR 2025; DataComp-LM will be presented at NeurIPS 2024; MobileCLIP will be presented at CVPR 2024; TiC-CLIP will be presented at ICLR 2024.
Research Experience
- Joined Apple as a machine learning researcher in 2021; has been involved in several projects related to efficiently running AI models on mobile devices.
Education
- Completed his PhD from the University of Toronto in 2021, with a focus on developing fast and robust training methods.
Background
- A machine learning researcher at Apple, focusing on enhancing the efficiency of foundation model training, particularly in improving the quality and effectiveness of training datasets, developing techniques for on-device foundation model training, and designing benchmarks and novel strategies for large-scale continual learning.
Miscellany
- Personal interests and additional information not provided.
