Gang Luo, PhD
Health/clinical informatics (data/predictive analytics and software system design/development), big data, machine learning, data mining, information retrieval, and database systems.
Prof. Luo’s research interests include health/clinical informatics (data/predictive analytics and software system design/development), big data, machine learning, data mining, information retrieval, and database systems with a focus on health applications. He invented the first method for automatically providing rule-based explanations for any machine learning model’s prediction/classification results with no accuracy loss, the questionnaire-guided intelligent medical search engine iMed, intelligent personal health record, and SQL and compiler progress indicators.
He received a Bachelor’s degree in Computer Science from Shanghai Jiaotong University, P.R. China, and a Ph.D. degree in Computer Science with a minor in Mathematics at the University of Wisconsin-Madison. Between 2004 and 2012, he was a Research Staff Member at the IBM T.J. Watson research center. Between 2012 and 2016, he was a faculty member in the Department of Biomedical Informatics at the University of Utah.
Currently accepting new MS, PhD, and Post-doc students.
G. Luo. Automatically Explaining Machine Learning Prediction Results: A Demonstration on Type 2 Diabetes Risk Prediction. Health Information Science and Systems, Vol. 4, No. 2, Mar. 2016, pp. 1-9.
X. Zeng, G. Luo. Progressive Sampling-Based Bayesian Optimization for Efficient and Automatic Machine Learning Model Selection. Health Information Science and Systems, Vol. 5, No. 1, Article 2, Sep. 2017, pp. 1-21.
G. Luo. Progress Indication for Machine Learning Model Building: A Feasibility Demonstration. SIGKDD Explorations, Vol. 20, No. 2, Dec. 2018.
G. Luo, C. Tang, and S.B. Thomas. Intelligent Personal Health Record: Experience and Open Issues. Journal of Medical Systems, Vol. 36, No. 4, Aug. 2012, pp. 2111-2128.
G. Luo, P. Tarczy-Hornoch, A.B. Wilcox, and E.S. Lee. Identifying Patients Who are Likely to Receive Most of Their Care from a Specific Health Care System: Demonstration via Secondary Analysis. JMIR Medical Informatics, Vol. 6, No. 4, e12241, Oct.-Dec. 2018, pp. 1-12.
G. Luo, C. Tang, and Y. Tian. Answering Relationship Queries on the Web. Proc. 2007 Int. World Wide Web Conf., Banff, Canada, May 2007, pp. 561-570.
G. Luo, J.F. Naughton, C.J. Ellmann, and M.W. Watzke. Toward a Progress Indicator for Database Queries. Proc. 2004 ACM-SIGMOD Int. Conf. on Management of Data, Paris, France, June 2004, pp. 791-802.