Institute for Information Sciences

Zijun Yao

Assistant Professor
Primary office:
Eaton Hall, 2048


Summary

I am an assistant professor at University of Kansas. Before that I was a research staff member at IBM research working on AI for healthcare. I received my Ph.D. in Information Technology from Rutgers University in 2018 supervised by Prof. Hui Xiong. My research interests include data mining and its broad range of applications on health informatics, mobile intelligence, and natural language processing.

For perspective students:

[RA/TA positions available] We are recruiting self-motivated PhD students to join us. Please feel free to email me your CV if you are interested in research of data mining and its broad applications. KU is the state’s flagship university and the member of the Association of American Universities (AAU). According to Carnegie Classification of higher education, KU is ranked Research I (R1) as the university with the highest levels of research activity. More application information of EECS can be found at link. Pease feel free to share the ads if you know someone would be interested [ads].

Education

Ph.D. in Information Technology (2018) Rutgers, the State University of New Jersey, NJ

M.S. in Computer Engineering (2011) Northeastern University, MA

B.E. in Electrical Engineering (2009) Guangdong University of Technology, China

Selected Publications

Conference papers:

  • Discovering Urban Functions of High-Definition Zoning with Continuous Human Traces

Chunyu Liu, Yongjian Yang, Zijun Yao, Yuanbo Xu, Weitong Chen, Lin Yue, Haomeng Wu

ACM International Conference on Information and Knowledge Management (CIKM), 2021.

  • Deep Staging: An Interpretable Deep Learning Framework for Disease Staging

Liuyi Yao, Zijun Yao, Jianying Hu, Jing Gao, Zhaonan Sun

IEEE International Conference on Healthcare Informatics (ICHI), 2021. [Paper]

  • Phenotypical Ontology Driven Framework for Multi-Task Learning

Mohamed Ghalwash, Zijun Yao, Prithwish Chakrabotry, James Codella, Daby Sow

ACM Conference on Health, Inference, and Learning (CHIL), 2021. [Paper]

  • eXITs: An Ensemble Approach for Imputing Missing EHR Data

James Codella, Hillol Sarker, Prithwish Chakraborty, Mohamed Ghalwash, Zijun Yao, Daby Sow

IEEE International Conference on Healthcare Informatics (ICHI), 2019.

  • Discovering Urban Travel Demands through Dynamic Zone Correlation in Location-Based Social Networks

Wangsu Hu, Zijun Yao, Sen Yang, Shuhong Chen, Peter J. Jin

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2018.

  • Representing Urban Functions through Zone Embedding with Human Mobility Patterns

Zijun Yao, Yanjie Fu, Bin Liu, Wangsu Hu, Hui Xiong

International Joint Conference on Artificial Intelligence (IJCAI), 2018. [Paper]

  • Dynamic Word Embeddings for Evolving Semantic Discovery

Zijun Yao, Yifan Sun, Weicong Ding, Nikhil Rao, Hui Xiong

ACM International Conference on Web Search and Data Mining (WSDM), 2018. [Paper] [Poster]

  • POI Recommendation: A Temporal Matching between POI Popularity and User Regularity

Zijun Yao, Yanjie Fu, Bin Liu, Yanchi Liu, Hui Xiong

IEEE International Conference on Data Mining (ICDM), 2016. (Full paper) [Paper]

  • The Impact of Community Safety on House Ranking

Zijun Yao, Yanjie Fu, Bin Liu, Hui Xiong

SIAM International Conference on Data Mining (SDM), 2016. [Paper] [Poster]

  • Sparse Real Estate Ranking with Online User Reviews and Offline Moving Behaviors

Yanjie Fu, Yong Ge, Yu Zheng, Zijun Yao, Yanchi Liu, Hui Xiong, Nicholas Jing Yuan

IEEE International Conference on Data Mining (ICDM), 2014.

  • Exploiting Geographic Dependencies for Real Estate Appraisal

Yanjie Fu, Hui Xiong, Yong Ge, Zijun Yao, Yu Zheng, Zhi-Hua Zhou

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2014.

  • User Preference Learning with Multiple Information Fusion for Restaurant Recommendation

Yanjie Fu, Bin Liu, Yong Ge, Zijun Yao, Hui Xiong

SIAM International Conference on Data Mining (SDM), 2014.

  • Learning Geographical Preferences for Point-of-Interest Recommendation

Bin Liu, Yanjie Fu, Zijun Yao, Hui Xiong

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2013.

Journal papers:

  • Multi-View Multi-Task Campaign Embedding for Cold-Start Conversion Rate Forecasting

Zijun Yao, Deguang Kong, Miao Lu, Xiao Bai, Jian Yang, Hui Xiong

IEEE Transactions on Big Data (TBD), 2022. [Paper]

  • Computing Co-location Patterns in Spatial Data with Extended Objects: a Scalable Buffer-based Approach

Yong Ge, Zijun Yao, Huayu Li

IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.

  • Modeling of Geographical Dependencies for Real Estate Ranking

Yanjie Fu, Hui Xiong, Yong Ge, Yu Zheng, Zijun Yao, Zhi-Hua Zhou

ACM Transactions on Knowledge Discovery from Data (TKDD), Vol.11, No.1, pp.1-27, 2016.

  • A General Geographical Probabilistic Factor Model for Point of Interest Recommendation

Bin Liu, Hui Xiong, Spiros Papadimitriou, Yanjie Fu, Zijun Yao

IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol.27, No.5, pp.1167–1179, 2015.

Archive:

  • ODVICE: An Ontology-Driven Visual Analytic Tool for Interactive Cohort Extraction

Mohamed Ghalwash, Zijun Yao, Prithwish Chakrabotry, James Codella, Daby Sow

In arXiv:2005.06434. [Paper]

Selected Awards & Honors

• IBM Research Accomplishments Award, 2020

• IBM First Patent Application Innovation Achievement Award, 2020

• International Joint Conferences on Artificial Intelligence (IJCAI) Travel Award, 2018

• ACM International Conferences on Web Search and Data Mining (WSDM) Travel Award, 2018 • IEEE International Conferences on Data Mining (ICDM) Travel Award, 2016

• SIAM International Conferences on Data Mining (SDM) Travel Award, 2016

• Dean’s Scholarship for Summer Research, Rutgers University, 2014


KU Today
One of 34 U.S. public institutions in the prestigious Association of American Universities
44 nationally ranked graduate programs.
—U.S. News & World Report
Top 50 nationwide for size of library collection.
—ALA
5th nationwide for service to veterans —"Best for Vets: Colleges," Military Times