Chuanren Liu is an Associate Professor in the Business Analytics and Statistics Department at the University of Tennessee, Knoxville.
His research interests include data mining and knowledge discovery, and their applications in business analytics.
He has published papers in refereed journals and conference proceedings, such as IEEE Transactions on Knowledge and Data Engineering, INFORMS Journal on Computing, European Journal of Operational Research, Annals of Operations Research, Information Sciences, Knowledge and Information Systems and SIGKDD, ICDM, SDM, AAAI, IJCAI, UbiComp, IEEE BigData, DSAA, etc.
Chuanren Liu received the Ph.D. in Management (Information Technology) from Rutgers, the State University of New Jersey, USA, the M.S. degree in Mathematics from the Beijing University of Aeronautics and Astronautics (BUAA), and the B.S. degree in Mathematics from the University of Science and Technology of China (USTC).
Editorial Board- Guest Editor: Special Issue on Domain-Driven Data Mining (JDSA)
- Guest Editor: Special Issue on Data-Intensive Research in Ecommerce (ECRA)
- Electronic Commerce Research and Applications
Education- 2011-2015: Ph.D., Management Science and Information Systems, Rutgers Business School
- 2008-2010: M.S., Mathematics, Beijing University of Aeronautics and Astronautics
- 2004-2008: B.S., Mathematics and Applied Mathematics, University of Science and Technology of China
Experience- 2019-: Assistant Professor, Business Analytics and Statistics, University of Tennessee, Knoxville
- 2015-2019: Assistant Professor, Decision Sciences, Drexel University
- 2014: Summer Intern, IBM Thomas J. Watson Research Center.
- 2013: Summer Intern, NEC Laboratories America.
- 2011-2014: Research Assistant, Data Mining and Business Analytics, Rutgers University
Membership- Association for Computing Machinery (ACM)
- Institute for Operations Research and the Management Sciences (INFORMS)
- Institute of Electrical and Electronics Engineers (IEEE, Senior Member)
- Society for Industrial and Applied Mathematics (SIAM)
Program Committee- IEEE International Conference on Data Mining, 2015 (Registration Chair), 2018-2022
- ACM SIGIR Conference on Research and Development in Information Retrieval, 2020-2022
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2015-2022
- AAAI Conference on Artificial Intelligence, 2019, 2020, 2021-2022 (SPC)
- International Joint Conference on Artificial Intelligence, 2016, 2021 (SPC), 2022
- INFORMS Workshop on Data Science, 2017-2022
- ACM International Conference on Web Search and Data Mining, 2021, 2022
- IEEE International Conference on Big Data, 2019-2021
- International Conference on Information and Knowledge Management, 2017-2020
- Syngenta Crop Challenge in Analytics Prize Committee, 2020
- International Conference on Big Data Computing and Communication, 2015, 2016, 2018
- SIAM International Conference on Data Mining, 2017
- International Conference on Data Analytics, 2015, 2016
- International Conference on Database Systems for Advanced Applications, 2016
- IEEE International Conference on Healthcare Informatics, 2015, 2016
Review- International Journal of Data Science and Analytics
- ACM Transactions on Intelligent Systems and Technology
- IEEE Transactions on Intelligent Transportation Systems
- IEEE Transactions on Neural Networks and Learning Systems
- Management Information Systems Quarterly
- Information Systems Research
- Management Science
- IEEE Transactions on Knowledge and Data Engineering
- Decision Sciences
- INFORMS Journal on Computing
- European Journal of Operational Research
- Journal of the Operational Research Society
- IEEE Transactions on Big Data
- Computer Communications
- ACM Transactions on Knowledge Discovery from Data
- Knowledge and Information Systems
- IEEE/ACM Transactions on Computational Biology and Bioinformatics
- ACM Transactions on Management Information Systems
- Data Mining and Knowledge Discovery
- Expert Systems With Applications
- IBM Journal of Research and Development
- International Journal of Automation and Computing
Teaching- STAT 632: Data Mining for Managers, Drexel University
- STAT 642: Data Mining for Business Analytics, Drexel University, 2016-2019
- STAT 610: Statistics for Business Analytics, Drexel University, 2015-2018
- Assistant, Statistical Methods in Business, Rutgers University, 2014 Spring
- Instructor, Business Research Methods (undergraduate level), Rutgers University, 2012 Summer
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