About

Bee-Chung Chen is a Senior Machine Learning Architect and Software Engineer at Pinterest, where she is responsible for developing and implementing AI technologies. With over 15 years of experience in data mining and analysis, Chen has made significant contributions to the field of recommendation algorithms, having designed algorithms that power the LinkedIn news feed, job recommendation, and article recommendation, as well as key Yahoo! sites including Yahoo! homepage and Yahoo! News. Chen's research in this field has resulted in over 20 academic papers published in top-tier conferences such as CACM, KDD, WWW, WSDM, ICDM, and EMNLP. Her expertise also extends to utilizing machine learning and statistical modeling to improve data analysis capabilities of data warehouses, and privacy analysis in data publication, which has resulted in over 10 papers published in conferences such as VLDB, SIGMOD, and journals like TKDD, VLDB J. and DMKD. Chen holds a Ph.D. in Computer Science from the University of Wisconsin-Madison, where she also earned a Bachelor's degree in Computer Science and Information Engineering. She also holds a Master's degree in Computer Science and Information Engineering from National Taiwan University. In addition to her work at Pinterest, Chen has also held senior positions at LinkedIn, where she served as a Distinguished Engineer in AI and Machine Learning, and Principal Staff Engineer and Applied Researcher. Chen's specialties include data mining and analysis, scalable analytic computation, web recommendation systems, and privacy-preserving data mining. She has authored a book on Statistical Methods for Recommender Systems and a survey paper on privacy-preserving data mining. Chen's technical skills include expertise in AI, ML, software engineering, recommendation systems, research scientist, web design, and C programming.