Scholar
Shuvendu Roy
Google Scholar ID: 5-zu4ZsAAAAJ
Queen's University | RBC Borealis; Former: Student Researcher @Google, Intern @Vector Institute
Citations & Impact
Citations
795
H-index
11
i10-index
13
Publications
20
Co-authors
7
list available
Publications
Resume (English only)
Academic Achievements
- Published 35+ papers in top-tier venues including ICLR, AAAI, TMLR, and ICASSP
- Authored 15+ top-tier publications during PhD studies
- Achieved state-of-the-art performance in medical foundation models at Vector Institute, resulting in five publications
- Developed cost-efficient self-supervised learning methods at Google Research with significant performance gains
- Published key works on few-shot class-incremental learning (TMLR’24) and few-shot tuning (TMLR’25)
Background
- AI Scientist with over 8 years of research and industry experience
- Specializes in large language models (LLMs), generative models, multi-modal learning, and unsupervised learning
- Contributed to impactful AI projects at Google Research, Borealis AI, and Vector Institute
- Published 35+ papers in top-tier venues (e.g., ICLR, AAAI, TMLR, ICASSP) on self-supervised learning, few-shot tuning, and computer vision
- Proficient in scaling ML solutions using Python, PyTorch, TensorFlow, and JAX
- Passionate about collaborating with talented teams to solve challenging problems with AI
