Welcome to Intelligent Data Science and Applications Lab π
In today's world, we are experiencing an explosion of information. Every day, over 2 million blog posts, more than a thousand academic papers, and 3 million Youtube videos are uploaded. With this increasing volume of information, we often face challenges in finding the optimal information, whether itβs deciding what to eat, what to wear, or which papers to read. Simply says, we are overwhelmed by vast amounts of information.
Our mission is to develop intelligent systems that empower individuals to navigate this overwhelming sea of information effectively. We aim to deliver relevant, high-quality, and actionable insights tailored to each user's unique context and needs.
Research Areas (Details)
Our group works on a wide range of topics related to data science, artificial intelligence, and large language models. Our major current focus is on recommender system, information retrieval, and data/web mining.
Open Positions
We are seeking self-motivated graduate students (MS/PhD) and undergraduate research interns. Please refer to this if you are interested in our research.
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Recent News
2025
Accepted paper: "Embracing Plasticity: Balancing Stability and Plasticity in Continual Recommender Systems", SIGIR, July 2025
Accepted paper: "Personalized Preference Reasoning with Large Language Models for Accurate and Explainable Recommendation", SIGIR, July 2025
Accepted paper: "Uncertainty Quantification and Decomposition for LLM-based Recommendation", WWW, May 2025
Accepted paper: "Chain-of-Factors Paper-Reviewer Matching", WWW, May 2025
Accepted paper: "Improving Scientific Document Retrieval with Concept Coverage-based Query Set Generation", WSDM, March 2025
Accepted paper: "Unsupervised Robust Cross-Lingual Entity Alignment via Neighbor Triple Matching with Entity and Relation Texts", WSDM, March 2025
Professional service: Prof. Kang has been invited to be a PC member of KDD, WWW, AAAI, SIGIR, and ACL (-SRW)