Scholar
Tao LIN
Google Scholar ID: QE9pa_cAAAAJ
Westlake University | EPFL
Citations & Impact
Citations
5,335
H-index
31
i10-index
41
Publications
20
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Multiple papers accepted by top international conferences such as NeurIPS 2025, CVPR 2025, ICLR 2025; Yuxuan's work CPathAgent was accepted by NeurIPS 2025; Yongxin GUO had three first-author papers accepted by ICLR 2025; Peng SUN's paper on Ideal Data was accepted by NeurIPS 2024.
Research Experience
- Currently leading the LINs Lab at Westlake University. Research focuses on designing efficient and robust deep learning methods through theoretical and empirical understandings.
Background
- Research Interests: The intersection of optimization and generalization for deep learning, including theoretical/empirical understanding (e.g., loss landscape, training dynamics), designing efficient & robust methods (both learning and inference) for deep learning (centralized) and collaborative deep learning (distributed and/or decentralized), especially under imperfect environments (e.g., noisy, heterogeneous, and hardware-constrained). Professional Field: Deep Learning, Optimization.
Miscellany
- Lab Activities: Running a research seminar on Deep Learning and Optimization.
Co-authors