While Large Language Models (LLMs) have revolutionized AI with their remarkable general knowledge capabilities, they face a critical challenge: the inability to truly understand you as an individual. Their one-size-fits-all paradigm fails to capture user's unique emotions, writing style, and personal preferences—leaving a significant gap between artificial intelligence and authentic personalization.

This gap represents both a challenge and an extraordinary opportunity. In an era where LLMs are reshaping technology, user personalization has become the next frontier, with transformative applications spanning conversational AI, recommendation systems, education, and healthcare.

In this talk, she will introduce Personalized Large Language Models (PLLMs)—an emerging research topic that harnesses individual data, from personal profiles to conversation history, creating AI that doesn't just respond, but truly resonates with each user's unique needs. Specifically, she will go through the latest breakthrough developments in this rapidly evolving field and explore the exciting possibilities ahead, revealing how PLLMs are poised to transform our relationship with AI from generic interactions to deeply personalized experiences.

Jiahong Liu is a Ph.D. candidate at The Chinese University of Hong Kong, supervised by Prof. Irwin King. Her research interests center on personalization techniques, including utilizing hyperbolic geometry to enhance foundation models and address data heterogeneity among users in domains such as recommender systems and federated learning. She has published several papers in top-tier conferences and journals, including ICDE, KDD, WebConf, AAAI, and Information Sciences. She also serves as a reviewer for multiple conferences and journals, including NeurIPS, ICML, ICLR, KDD, and others.