Joonseok Lee is a research engineer in Video Content Analysis team, in Machine Perception at Google Research. He is mainly working on content-based YouTube Video Recommendation, utilizing video features extracted using Google Brain. He earned his Ph. D. in Computer Science from Georgia Institute of Technology in August 2015, under the supervision of Dr. Guy Lebanon and Prof. Hongyuan Zha. His thesis is about local approaches for collaborative filtering, with recommendation systems as the main application. He has done three internships during Ph.D, including Amazon (2014 Summer), Microsoft Research (2014 Spring), and Google (2013 Summer). Before coming to Georgia Tech, he worked in NHN corp. in Korea (2007-2010). He received his B.S degree in computer science and engineering from Seoul National University, Korea. His paper "Local Collaborative Ranking" received the best student paper award from the 23rd International World Wide Web Conference (2014). He has served as a program committee in many conferences including NIPS, AAAI, WSDM, and CIKM, and journals including JMLR, ACM TIST, and IEEE TKDE. He co-organized the CVPR'17 Workshop on YouTube-8M Large-Scale Video Understanding as a program chair, and served as the publicity chair for AISTATS 2015 conference. He is currently serving as a reviewer for Google Faculty Research Awards Program. More information is available in his website (