The First International Workshop on Learning-assisted Algorithm Design (LEAD 2026) will be held as part of the IJCAI-ECAI 2026 conference in Bremen, Germany (August 15–17, 2026). The workshop aims to bring together researchers working at the intersection of machine learning, optimization, evolutionary computation, and automated algorithm design, with a focus on learning-driven approaches for algorithm configuration, selection, and analysis.

Topics of interest include reinforcement learning for algorithm configuration, hyper-heuristics, meta-black-box optimization, surrogate modelling, large language models for algorithm design, exploratory landscape analysis, benchmarking methods, and related applications. The workshop welcomes original research papers, work in progress, previously published work, and position papers, encouraging open discussion and collaboration in the growing LEAD research community.

The workshop is co-organized by Yue-Jiao Gong, Tome Eftimov, Zhiguang Cao, Ran Cheng, Kai Wu, André Hottung, Fei Liu, Xueming Yan, Zeyuan Ma, and Hongshu Guo.

More information and submission details are available on the workshop website: https://sites.google.com/view/lead-ijcai-ecai2026