Zijun Yao
About
I am an Assistant Professor at University of Kansas (KU) in the Department of Electrical Engineering and Computer Science (EECS). My research focuses on data mining and knowledge discovery, with an emphasis on creating effective and efficient data science techniques for emerging data-intensive applications. In particular, my current research focuses in the domains of health informatics, recommender systems, and natural language processing. More recently, my research involves utilizing Large Language Models (LLMs) for AI-generated Content (AIGC) detection, and LLM-in-the-loop algorithm development. Prior to joining KU as an Assistant Professor in the Department of EECS, I was a research staff member in AI for healthcare at IBM Research working under the supervision of Dr. Jianying Hu on modeling the progression of Huntington Disease (HD) in collaboration with the CHDI Foundation. Previously, I received my Ph.D. in Information Technology from Rutgers University in 2018, under the guidance of Dr. Hui Xiong, focusing on spatio-temporal pattern mining using massive GPS data. During my academic journey, I also gained valuable experience as a research intern at Yahoo Research and Technicolor AI Lab, collaborating with Deguang Kong, Yifan Sun, Nikhil Rao, and Weicong Ding.
Research Performance Summary
First Recorded Paper
Learning geographical preferences for point-of-interest recommendation
Year: 2013
Citations: 546
Venue: Proceedings of the 19th ACM SIGKDD international conference on Knowledge
Latest Recorded Paper
User-Adaptive Meta-Learning for Cold-Start Medication Recommendation with Uncertainty Filtering
Year: 2026
Citations: 0
Venue: arXiv preprint arXiv:2601.22820
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.