Qingquan Song

Dr. Qingquan Song is a machine learning and relevance engineer in the AI Foundation team at LinkedIn. He received his PhD in computer science from Texas A&M University. His research interests are automated machine learning, dynamic data analysis, tensor decomposition, and their applications in recommender systems and social networks. He is one of the authors of AutoKeras. His papers have been published at major data mining and machine learning venues, including KDD, NeurIPS, Transactions on Knowledge Discovery from Data (TKDD), and others.