The Information Retrieval and Recommendation Laboratory (IR² Lab) is committed to advancing intelligent information access through innovative research in information retrieval, recommender systems, and personalized data-driven technologies. Our mission is to develop robust, efficient, and responsible algorithms that enhance how users search, discover, and interact with information across diverse domains. Focusing on areas such as multi-criteria recommendation, neural retrieval, user modeling, privacy-preserving computation, fairness, and system robustness, the lab aims to produce impactful theoretical contributions as well as practical solutions. Through interdisciplinary collaboration and real-world experimentation, IR² Lab strives to empower academia, industry, and society with next-generation retrieval and recommendation technologies.