Interests:

Health/clinical informatics (data/predictive analytics and software system design/development), big data, machine learning, data mining, information retrieval, and database systems.

Background:

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, machine learning, 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.

Teaching:

Currently accepting new MS, PhD, and Post-doc students.

Research:

Dr. Luo’s research focuses on developing new machine learning, data mining, information retrieval, and database methods to help solve healthcare problems. Examples of his work include constructing the world’s most accurate models for predicting asthma hospital encounters in patients with asthma, creating the world’s first model for predicting appropriate admission of bronchiolitis patients in the emergency department, building intelligent medical search engines, and developing efficient and automatic tools for machine learning model selection.

Representative publications:

G. Luo, M.D. Johnson, F.L. Nkoy, S. He, and B.L. Stone. Automatically Explaining Machine Learning Prediction Results on Asthma Hospital Visits in Patients with Asthma: Secondary Analysis. JMIR Medical Informatics, Vol. 8, No. 12, e21965, 2020.

G. Luo, S. He, B.L. Stone, F.L. Nkoy, and M.D. Johnson. Developing a Model to Predict Hospital Encounters for Asthma in Asthmatic Patients: Secondary Analysis. JMIR Medical Informatics, Vol. 8, No. 1, e16080, 2020.

Q. Dong, G. Luo. Progress Indication for Deep Learning Model Training: A Feasibility Demonstration.IEEE Access, Vol. 8, 2020, pp. 79811-79843.

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, 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, 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.