Changyue Song, a PhD student in the Department of Industrial and Systems Engineering, won the best paper award from the Quality, Statistics and Reliability Section of the Institute for Operations Research and the Management Sciences.
Song, who’s part of Associate Professor Kaibo Liu’s Lab for System Informatics and Data Analytics, received the honor at the 2019 INFORMS Annual Meeting in October in Seattle, where he presented his paper, titled “Collusion Detection and Ground Truth Inference in Crowdsourcing for Labeling Tasks.”
Another member of Liu’s lab, Di Wang, a visiting PhD student from Peking University in China, received the best student paper award from the organization’s Data Mining section for her paper titled “A Spatiotemporal Prediction Approach for A 3D Thermal Field from Sensor Networks.”