Yunqing LIU (刘云清)

Yunqing LIU (刘云清)

PhD candidate in PolyU

Talks and Tutorials

Data Engineering Meets Large Language Models: Challenges and Opportunities

May 19, 2025

Workshop, IEEE ICDE 2025, Hong Kong, China

This workshop on the synergy between Data engineering (DE) and Large Language Models (LLMs) is a pioneering event in top-tier conferences. It brings together experts to share recent challenges and opportunities, aiming to inspire future research. With oral presentations and poster sessions, the workshop provides a platform for researchers from natural language processing, data engineering, and database systems to discuss ideas, review past work, and explore new directions. The focus is on the synergy between LLMs and DBMS from two aspects. The first explores how LLMs empower DBMS tasks, such as data retrieval, query optimization, and index tuning. The second examines how DE enhance the capability of LLM through data engineering, retrieval-augmented generation (RAG) systems, multi-modal data management, and more. By including participants from academia and industry, the workshop aims to connect practical applications with research, encouraging collaboration that will shape the future of intelligent databases.

Recommender Systems in the Era of Large Language Models (LLMs)

December 03, 2023

Tutorial, IEEE ICDM 2023, Shanghai, China

With the prosperity of e-commerce and web applications, Recommender Systems (RecSys) have become an important component in our daily life, providing personalized suggestions that cater to user preferences. While Deep Neural Networks (DNNs) have made significant advancements in enhancing recommender systems by modeling user-item interactions and incorporating their textual side information, these DNN-based methods still have some limitations, such as difficulties in effectively understanding users’ interests and capturing textual side information, inabilities in generalizing to various seen/unseen recommendation scenarios and reasoning on their predictions, etc.