Biography

Prof. Steven C.H. Hoi is currently Managing Director of Salesforce Research Asia at Salesforce, located in Singapore. He has been also a tenured Associate Professor of the School of Information Systems at Singapore Management University, Singapore. Prior to joining SMU, he was a tenured Associate Professor of the School of Computer Engineering at Nanyang Technological University, Singapore. He received his Bachelor degree in Computer Science from Tsinghua University, Beijing, China, in 2002, and both his Master and PhD degrees in Computer Science and Engineering from the Chinese University of Hong Kong, in 2004 and 2006, respectively.

Prof Hoi is a researcher in machine learning and artificial intelligence. His research interests include machine learning (especially for deep learning and online learning) and their applications to a variety of real-world domains, including computer vision and pattern recognition, multimedia information retrieval, social media, web search and data mining, natural language processing, computational finance, etc . He has published over 200 high-quality referred journal and conference papers. He has contributed extensively in academic communities. He has served as the Editor-in-Chief (EiC) of Neurocomputing, General Co-chair for ACM SIGMM Workshops on Social Media (WSM'09-11), Program Co-Chair for Asian Conference on Machine Learning (ACML'12), Book editor for "Social Media Modeling and Computing", Guest editor for Machine Learning and ACM TIST journals, Associate Editor (AE) for several reputable journals including IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI), Area Chair/Senior PC/TPC for many conferences. He has been often invited for external grant review by worldwide funding agencies, including USA NSF agency, Hong Kong RGC agency, etc.

He was the recipient of the Lee Kuan Yew Fellowship Lee Kong for research excellence in 2018 and the Lee Kong Chian Fellowship Award in 2016. He was elevated to IEEE Fellow (Class of 2019) for his significant contributions to machine learning for multimedia information retrieval and scalable data analytics.