Scholar
Lucas Caccia
Google Scholar ID: fuvIITUAAAAJ
Microsoft Research
Citations & Impact
Citations
2,054
H-index
15
i10-index
18
Publications
20
Co-authors
13
list available
Publications
Resume (English only)
Academic Achievements
- Published a paper on building and reusing a library of PEFT experts at ICML 2024 in July 2024; Successfully defended Ph.D. in November 2023.
Research Experience
- Senior Researcher at Microsoft Research; Started a post-doc at MSR Montréal in 2023, continuing work on efficient adaptation.
Education
- Completed Ph.D. in 2023 from McGill University and Mila, advised by Joelle Pineau. PhD thesis focused on enabling efficient and robust Continual Learning in neural networks.
Background
- Research Interests: Building modular and composable agents; Professional Field: Decentralized, continual, and collaborative model development; Summary: Focused on enabling efficient and robust Continual Learning in neural networks through modularity.
Miscellany
- Personal Interests: Not provided
