主讲人
Joeran Beel
University of Siegen
时间
2026年3月10日 星期二
上午 10:00-11:30
地点
上海财经大学信管楼102会议室
Abstract
Recommender-systems research has accelerated model and evaluation advances, yet largely neglects automating the research process itself. We argue for a shift from narrow AutoRecSys tools -- focused on algorithm selection and hyper-parameter tuning -- to an Autonomous Recommender-Systems Research Lab (AutoRecLab) that integrates end-to-end automation: problem ideation, literature analysis, experimental design and execution, result interpretation, manuscript drafting, and provenance logging. Drawing on recent progress in automated science (e.g., multi-agent AI Scientist and AI Co-Scientist systems), we outline an agenda for the RecSys community: (1) build open AutoRecLab prototypes that combine LLM-driven ideation and reporting with automated experimentation; (2) establish benchmarks and competitions that evaluate agents on producing reproducible RecSys findings with minimal human input; (3) create review venues for transparently AI-generated submissions; (4) define standards for attribution and reproducibility via detailed research logs and metadata; and (5) foster interdisciplinary dialogue on ethics, governance, privacy, and fairness in autonomous research. Advancing this agenda can increase research throughput, surface non-obvious insights, and position RecSys to contribute to emerging Artificial Research Intelligence. We conclude with a call to organise a community retreat to coordinate next steps and co-author guidance for the responsible integration of automated research systems. Finally, we provide results from a first proof-of-concept tool that conducts recommender systems research (in parts) autonomously.
Biography
Joeran Beel is head of the Intelligent Systems Group at the University of Siegen. His research focuses on automated machine learning & meta-learning, information retrieval, and recommender systems. He has published more than 140 peer-reviewed publications, is a member of the ACM Recommender Systems Steering Committee, an associate editor and the information director at ACM TORS, and he acted as a reviewer for venues such as SIGIR, ECIR, RecSys, UMAP, ACM TiiS, and JASIST. Joeran Beel has founded multiple award-winning business start-ups and has initiated and contributed to various projects, including Recommender-Systems.com, Docear, TensorFlow, and JabRef. He acquired over 2.5 million Euros in funding for his research and business start-ups.
