Yikun Ban
Associate Professor
School of Computer Science and Engineering
Beihang University

I am a tenure-track associate professor in the School of Computer Science and Engineering at
Beihang University and a member of the State Key Laboratory of Software Development Environment. Previously, I was a postdoc and obtained my Ph.D. degree at
Computer Science, University of Illinois at Urbana-Champaign, where I was advised by Prof.
Jingrui He, Prof.
Hanghang Tong, and Prof.
Arindam Banerjee.
Prior to this, I obtained my Master's degree from
EECS, Peking University and
bachelor's degree from
Wuhan University.

I am interested in principled algorithms in the space of reinforcement learning and deep learning, to solve real-world sequential decision-making problems. Current research topics:
- Reinforcement Learning with Human Feedback
- Multi-Agent Reinforcement Learning
- Ensemble Learning of LLMs

yikunb[at]buaa.edu.cn, yikunb2[at]illinois.edu
Google Scholar

News
- 2025.5 Welcome to check our survey! A Survey on LLM Ensemble.
- 2025.5 NeurIPS 2025 Spotlight! Transformer Copilot: Introduces the new concept of a “Mistake Log” and a novel paradigm for LLM fine-tuning.
- 2025.5 NeurIPS 2025! SamS: Proposes the new problem of dynamic sample scheduling in preference optimization for LLMs, together with an RL-based solution.
- 2025.5 "LLM-Forest" is accepted by ACL 2025 Findings, a new prompt-based LLM Ensemble Learning approach.
- 2024.12 "PageRank Bandit" is accepted by NeurIPS 2024, in which we first use bandit perspective to solve link prediction.
- 2024.12 "Robust Neural Contextual Bandit" is accepted by NeurIPS 2024, in which we remove the Positive Definite assumption for NTK Matrix.