Biography

I am a postdoctoral research associate in the School of Information Sciences at the University of Illinois Urbana-Champaign (UIUC). I received my Ph.D. in Computer Science and Engineering from the University of Notre Dame under the supervision of Prof. Dong Wang. Before that, I got my M.S. in Data Science from Indiana University and attained my B.S. in Software Engineering from Wuhan University. I have also worked as the W. J. Cody Research Associates at Argonne National Laboratory. I have authored and co-authored 60+ peer-reviewed conference/journal papers in various highly competitive human-centered AI and social sensing and computing venues such as ACM CSCW, IEEE BigData, ACM/IEEE ASONAM, AAAI, IJCAI, ACM WWW, AAAI HCOMP, RTSS, IEEE TBD, IEEE TCSS, ACM/IEEE IWQoS, IEEE SECON, ACM RecSys, Elsevier KBS.

Research Interests

My research focuses on the Human-centered Artificial Intelligence (AI) and Social Sensing. In particular, my research aims to explicitly utilize the human intelligence from crowdsourcing systems (i.e., crowd intelligence) to effectively design, configure, and troubleshoot the AI models to improve the performance, fairness, explainability, and accountability of the AI models in social sensing applications.
I am delighted to design principled solutions that integrate the state-of-the-art crowdsourcing techniques (e.g., Amazon MTurk), AI models (e.g., convolutional/recurrent/graph neural network, generative adversarial network, transfer/contrastive learning), and estimation theoretical approaches (e.g., maximum likelihood estimation (MLE), subjective logic) to jointly model the diversified yet complementary AI and crowd intelligence to address a rich set of complex real-world problems including urban infrastructure monitoring, disaster damage assessment, traffic risk prediction, misinformation detection, etc.