Tucson (January 2, 2019) – Management Information Systems Assistant Professor Junming Yin and Gentile Family Professor Daniel Zeng of the University of Arizona Eller College of Management won the Best Paper Award at the 2018 Workshop on Information Technologies and Systems (WITS) conference.
The award-winning paper, “Towards Better Learning from Crowd Labeling:
A Variational Inference Approach,” examines the problem of learning from crowd labeling in the general multi-label setting, which can help businesses significantly reduce data acquisition cost.
WITS was launched in 1991 to focus on addressing complex business problems or societal issues using current and emerging information technologies. WITS rewards research that can change the way information technology functions (e.g., by designing, modifying or constructing systems) so that they can better solve real-world problems.
Yin earned his PhD from the University of California-Berkeley. His areas of expertise are statistical machine learning, probabilistic modeling and inference and nonparametric and high-dimensional statistical inference. Earlier this year, he also won the Adobe Digital Experience Research Award for a strategy to develop statistical machine learning methods to quickly match the right content to the right consumers. Zeng earned his PhD from Carnegie Mellon University. His areas of expertise include online surveillance, social computing, security informatics and software agents. He won a Best Paper Award at WITS in 2004.