A human-centered recommender system is a research-driven and practical approach that emphasizes understanding both recommender systems and user characteristics, as well as their interactions. The primary objective is to design algorithms and user experiences that enhance recommendation effectiveness. This chapter explores the evolution from traditional recommender systems to human-centered recommender systems, reviewing key studies and advancements. It highlights the opportunities and challenges in human-centered recommender systems and examines pathways for their integration and continuous evolution. Finally, the chapter anticipates future trends and developments in human-centered recommender systems.