Gloria Ai Hui Teng
Assistant Professor,
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Expertise Summary
Data analytics, statistical modeling and learning
Teaching Summary
Subjects taught in the past:
- Various general mathematics and statistics subjects for business, science, engineering and mathematics major.
- More specialized subjects including Applied Statistical Models, Generalized Linear Models, Financial Mathematics, and Actuarial Modeling.
Currently convening:
- Probability Models and Methods (Autumn)
- Multivariate Analysis (Spring)
- Mathematics Group Projects
Recent Publications
CHEN, I-CHUN, TENG, GLORIA, CHEN, CHUR-JEN, LAN, TSUO-HUNG and LIU, HUNG-JEN, 2020. The Autonomic Progress Bar Motivates Treatment Completion for Patients of Stimulant Use Disorder and Cannabis Use Disorder FRONTIERS IN PSYCHIATRY. 10,
SAINUDIIN, RAAZESH and TENG, GLORIA, 2019. Minimum distance histograms with universal performance guarantees JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE. 2(2), 507-527
SAINUDIIN, RAAZESH, TENG, GLORIA, HARLOW, JENNIFER and LEE, DOMINIC, 2013. Posterior Expectation of Regularly Paved Random Histograms ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION. 23(1),
TENG, GLORIA, KUHN, KENNETH and SAINUDIIN, RAAZESH, 2012. Statistical Regular Pavings to Analyze Massive Data of Aircraft Trajectories JOURNAL OF AEROSPACE COMPUTING INFORMATION AND COMMUNICATION. 9(1), 14-25
CHEN, I-CHUN, TENG, GLORIA, CHEN, CHUR-JEN, LAN, TSUO-HUNG and LIU, HUNG-JEN, 2020. The Autonomic Progress Bar Motivates Treatment Completion for Patients of Stimulant Use Disorder and Cannabis Use Disorder FRONTIERS IN PSYCHIATRY. 10,
SAINUDIIN, RAAZESH and TENG, GLORIA, 2019. Minimum distance histograms with universal performance guarantees JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE. 2(2), 507-527
SAINUDIIN, RAAZESH, TENG, GLORIA, HARLOW, JENNIFER and LEE, DOMINIC, 2013. Posterior Expectation of Regularly Paved Random Histograms ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION. 23(1),
TENG, GLORIA, KUHN, KENNETH and SAINUDIIN, RAAZESH, 2012. Statistical Regular Pavings to Analyze Massive Data of Aircraft Trajectories JOURNAL OF AEROSPACE COMPUTING INFORMATION AND COMMUNICATION. 9(1), 14-25