Chong Ho "Alex"ÌýYuÌýPH.D.
College of Natural and Computational Sciences - Department of Mathematics
Professor and Program Director of Data Science
Education:
- Ph.D. in Measurement, Statistics and Methodological Studies, Arizona State Å·ÃÀAƬ
- Ph.D. in Philosophy, Arizona State Å·ÃÀAƬ
- M.A. in Theology, Azusa Pacific Å·ÃÀAƬ
- M.Ed. in Educational Psychology, Å·ÃÀAƬ of Oklahoma
- MHR in Human Relations, Å·ÃÀAƬ of Oklahoma
- B.S. in Mass Communication, Bemidji State Å·ÃÀAƬ
- B.A. in Visual Arts, Bemidji State Å·ÃÀAƬ
- Graduate Certificate in Public Health, Å·ÃÀAƬ of Arizona
- Graduate Certificate in Liberal Studies, Hamline Å·ÃÀAƬ
- Certificate in History and Philosophy of Science, Arizona State Å·ÃÀAƬ
Courses Taught:
- MATH 1123: Statistics
- MATH 1130: Pre-Calculus I
- MATH 1140: Pre-Calculus II
- MATH 3460: Probability
- MATH 3470: Applied Statistics
- DSCI 6200: Data Science and Machine Learning
- DSCI 6300: Data Visualization
- DSCI 6400: Data Ethics
- DSCI 6700: Text Mining and Unstructured Data
Professional Interests:
Dr. Yu is highly interested in data science and machine learning (DSML). As the Vice President for Statistics Education and the President-elect of the Southern California Chapter of the American Statistical Association (SCASA), he enthusiastically shares the latest trends and news about data science and machine learning with the research community. He disseminates this through a weekly newsletter and by managing the statistics and data science newsroom on the SCASA’s website:
Teaching Interests/Research:
As an educator, Dr. Yu is committed to ensuring himself to stay up-to-date in the field so that he can provide students with the latest skills needed for careers and research. To accomplish this goal, he continuously seeks to evolve his own knowledge by attending conferences and workshops run by top data analytics companies like SAS Institute, Salesforce (Tableau), and Amazon Web Services. He also maintains connections with industry professionals to understand which methodologies are most in-demand. Dr. Yu believes this dedication to reinvention is crucial for empowering faculty to equip learners with cutting-edge, real-world expertise.
Dr. Yu is a three-time winner of the SAS faculty scholarship (2016, 2017 SAS Global Forum and 2017 Western Users of SAS Software Conference). In addition, he also won the Distinguished SAS Educator Award in 2021.
His research interests include, but are not limited to, alternate and emerging research methods (e.g., DSML, exploratory data analysis, data visualization, and item response theory), philosophical aspects of research methodologies (e.g., causal inferences, the nature of latent constructs, and abductive reasoning), and cross-cultural comparison in STEM education (e.g., Program for International Student Assessment [PISA], Program for International Assessment of Adult Competencies [PIAAC], and Trends for International Math and Science Study [TIMSS]).
He authored many books and articles on these topics. His recent publications on these topics are Data mining and exploration: From traditional statistics to modern data science (2022, CRC Press), Creating changes in science and math education: Lessons from Hong Kong (2020, Springer, coauthor: H. S. Lee), AI and Psychology (in press, Oxford Å·ÃÀAƬ Press), and Machine learning for analyzing the relationship between well-being and academic performance with large-scale assessment Data (in press, Springer). His research articles can be accessed at:
- Author’s own website:
- Google Scholar:
- Semantic Scholar:
- Research Gate:
Teaching Interests/Research:
Hiking, photography, travel
