Yu (Jeffrey) Hu

Yu (Jeffrey) Hu is an American computer scientist and engineer, best known for his contributions to the fields of recommender systems, machine learning, and data mining, particularly in the context of music and social networks.

Hu received a Ph.D. in Computer Science from Cornell University. His research often focuses on developing novel algorithms and models for personalized recommendations, user behavior analysis, and social network analysis. His work has been influential in both academic research and industrial applications.

A significant portion of his career has been spent at Yahoo! Research, where he served as a Research Scientist. His research at Yahoo! focused on areas such as large-scale machine learning, recommender systems for music, and social advertising. He has published extensively in top-tier computer science conferences and journals, including the Conference on Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD).

Hu's research contributions often address the challenges of large-scale data processing, user preference modeling, and the cold-start problem in recommender systems. His work has influenced the development of algorithms used by various companies in the tech industry for personalization and recommendation tasks. He is also known for his work on developing scalable algorithms for matrix factorization and other machine learning techniques suitable for large datasets.