معرفی
Yikun Ban is a tenure-track Associate Professor in the School of Computer Science and Engineering at Beihang University, where he is a member of the State Key Laboratory of Software Development Environment. He earned his PhD in Computer Science from the University of Illinois Urbana-Champaign (2023), MS in Computer Science from Peking University (2019), and BS in Software Engineering from Wuhan University (2016).
- PhD: University of Illinois Urbana-Champaign (2023)
- MS: Peking University (2019)
- BS: Wuhan University (2016)
His research focuses on principled algorithms for reinforcement learning with human feedback, neural contextual bandits, and exploration-exploitation problems. He develops frameworks combining deep learning with bandit theory for applications in recommendation systems, disinformation detection, and dynamic graph learning.
Recent publications address:
- Robust neural contextual bandits (NeurIPS 2024)
- Graph neural bandits (KDD 2023)
- Meta-learning for bandit scheduling (NeurIPS 2023)
- Clustering in contextual bandits (WWW 2021, AAAI 2021)
Honors include the NeurIPS Scholar Award and recognition as ICML Outstanding Reviewer.
His open-source LOCB repository provides Python implementations for contextual multi-armed bandit algorithms with local clustering, supporting applications in recommendation systems and online learning.
