Organizers

• Dr. Irene Li ([email protected]) is the main point of contact for the workshp. She is a Project Assistant Professor at the University of Tokyo. Her primary research focuses on natural language processing and artificial intelligence, with a particular emphasis on medical and clinical texts, alongside educational applications. She actively contributes to leading conferences such as ACL, NAACL, EMNLP, and AAAI through publications and program committee roles. Moreover, she has been the lead organizer of various online and in-person seminars for over three years, with one event drawing around 300 participants. She was among the co-authors of the Best Student Paper at RecSys 2023. She was also the principal organizer of the first EARL workshop at RecSys 2024.
• Dr. Ruihai Dong ([email protected]) is an Assistant Professor at the University College Dublin. His research interests lie in Machine Learning and Deep Learning, and their applications in recommender systems and finance. Ruihai has published in top peer-reviewed journals and leading conferences such as WWW, RecSys, IUI, ACL, IJCAI, etc., and also has served on the program committee for various conferences, including ACL, AAAI, ECML, EMNLP, etc. He was also a co-author of the Best Student Paper Award at RecSys 2023. He was a founder and organizer of the Deep Learning meetup in Dublin and organized a series of events sponsored by multiple industry supporters, including Zalando, Accenture, Deloitte, etc.
• Dr. Guillaume Salha-Galvan ([email protected]) is an incoming Associate Professor at Shanghai Jiao Tong University. He previously served as the Director of Machine Learning Research at Kibo Ryoku, and as a Research Scientist and Coordinator for Music Recommendation at Deezer. His research interests include graph learning, recommender systems, LLMs, and their music-related applications. He regularly publishes and serves as a reviewer in peer-reviewed journals and leading conferences such as ICML, KDD, WWW, IJCAI, and RecSys. In particular, he has co-authored eight articles in the past five RecSys editions, including works nominated for Best Short Paper at RecSys 2020, Best Student Paper at RecSys 2021, and Best Full Paper at RecSys 2024.
• Dr. Aonghus Lawlor ([email protected]}) is an Assistant Professor in the School of Computer at UCD and Funded Investigator in the Insight Centre for Data Analytics. The Insight Centre for Data Analytics is one of Europe’s largest data analytics research organisations, with 400+researchers, more than 80 industry partners and over €100m in funding. His current research interests are in recommender systems and machine/deep learning, and the application of computer vision for medical imaging. He has worked on several large scale industry projects and EU projects, developing novel recommender systems approaches to many application domains. This work has led to publications in top conferences and multiple patents.
• Dr. Dairui Liu ([email protected]) is a Post-doctoral Research Fellow at University College Dublin. His research focuses on natural language processing and recommender systems, specializing in explainable news recommendations. Recently, he has spearheaded the development of privacy-by-design and governed recommendation frameworks at Huawei Ireland Research Centre. He has published extensively in top-tier venues, including ACL, RecSys, CIKM, TORS, and ICCBR. He actively contributes to the academic community as a reviewer for prestigious conferences (e.g., ACL, RecSys) and journals (e.g., TOIS, TORS). He was also a co-author of the Best Student Paper at RecSys 2023.
• Dr. Lei Li ([email protected]) is a Postdoctoral Research Fellow at Hong Kong Baptist University, specializing in recommender systems and natural language processing. His recent research focuses on leveraging LLMs for recommendation systems, supported by the Hong Kong Research Grants Council (RGC) and Huawei. His work in this area includes LLM-based explainable recommendation, efficient LLMs for recommendation, and a survey on LLM-driven recommendation techniques. He has served as a Program Committee member for RecSys and WWW, a reviewer for leading journals such as TKDE, TOIS, TORS, and TBD, and a guest editor for a TORS special issue on "Large Language Models for Recommender Systems." Additionally, he co-presented a tutorial on LLM-based recommendation at RecSys 2023, titled "Large Language Models for Recommendation", which attracted hundreds of attendees.