Data Quality and Learning with Crowdsourcing
Victor S. Sheng received the M.Sc. degree from the University of New Brunswick, Fredericton, NB, Canada, and the Ph.D. degree from the University of Western Ontario, London, ON, Canada, both in computer science, in 2003 and 2007, respectively. He is an Associate Professor of computer science and the Founding Director of Data Analytics Laboratory at University of Central Arkansas. After receiving the Ph.D. degree, he was an Associate Research Scientist and NSERC Postdoctoral Fellow in information systems with the Stern Business School at New York University. His research interests include data mining, machine learning, crowdsourcing, and related applications in business, industry, medical informatics, and software engineering. He has published more than 140 research papers in conferences and journals of machine learning and data mining. Most papers are published in top journals and conferences in data science, such as PAMI, TNNLS, TKDE, JMLR, AAAI, KDD, IJCAI, and ACMMM. Prof. Sheng is a senior member of IEEE. He is a conference organizer for several conferences, and an editorial board member for several journals. He also is a SPC and PC member for many international conferences (such as IJCAI, AAAI, and KDD) and a reviewer of more than twenty international journals (such as PAMI, TNNLS, TKDE, and JMLR). He was the recipient of the Best Paper Award Runner Up from KDD’08, the Best Paper Award from ICDM’11, the Best Student Paper Award Finalist from WISE’15, and the Best Paper Award from ICCCS’18.