Efficient Learning Laboratory

Sungkyunkwan University

Welcome to ELLab! We are interested in building efficient deep learning models and algorithms.

Research Topics

We aim to enhance the efficiency of deep learning across various AI fields. We primarily focus on developing data-efficient algorithms and applying them to real-world problems. Key topics include:
  • Self-supervised learning, few-shot learning, meta-learning, transfer learning, continual learning,
  • Applications in computer vision (e.g., images), graphs (e.g., molecules), tabular data (e.g., financial/medical data).

How to Join?

We are always looking for highly motivated graduate (or internship) students with a strong interest in the area of deep learning. If you are interested in joining us, please check this page.

News

  • [2026-02] Two papers were accepted to CVPR 2026 (one in the Findings track).
  • [2026-01] Two papers were accepted to ICLR 2026.
  • [2026-01] One paper was accepted to EACL Findings 2026.
  • [2025-09] Two papers were accepted to NeurIPS 2025.
  • [2025-09] One paper was accepted to ACSAC 2025.
  • [2024-12] One paper was accepted to AAAI 2025.
  • [2024-04] One paper was accepted to CVPR 2024.
  • [2024-04] One paper was accepted to TMLR.
  • [2024-03] ELLab @ SKKU has been launched.