Yonggang “Tim” Lu, Ph.D.

Dr. Yonggang Lu is a Harold Alfond Associate Professor of Business Analytics in the Maine Business School at the University of Maine. Before joining UMaine, he was an Associate Professor of Quantitative Methods and Decision Sciences at the University of Alaska. Prior to Dr. Lu’s academic career, he worked at JPMorgan Chase Bank as a customer analytics specialist responsible for large-scale financial data mining and predictive modeling to support the bank’s marketing and risk management operations in the U.S. mortgage, home equity, and private student loan markets. He is a financial risk manager (FRM) certified by the Global Association of Risk Professionals.


  • Ph.D. Information Systems and Quantitative Sciences, Texas Tech University
  • M.S. Applied Mathematics, Texas Tech University
  • M.A. Economics, Texas Tech University
  • M.S. Finance, Texas Tech University
  • B.E. Chemical Process Equipment and Control Engineering, Xi’an Jiaotong University
  • B.A. Financial Economics, Xi’an Jiaotong University

Teaching Areas

  • Foundations of Business Intelligence and Analytics
  • Data Pre-processing for Business Analytics
  • Business Data Mining and Knowledge Discovery
  • Information Visualization
  • Problem Solving and Decision Analysis

Research Interests

Dr. Lu’s general area of research is data information modeling and knowledge learning in support of business decision making. His primary research interest is on TREE (Transparent, Reliable, Efficient and Effective) Bayesian analytic models for data information processing. He is especially interested in general-purpose Bayesian inference algorithms for regularizing machine and statistical learning models with subjective prior knowledge. His secondary research interest is in social network analysis for understanding online information diffusion.

Awards / Professional Accomplishments

  • Excellence in Research Award, Maine Business School, 2022
  • Faculty Mentor Impact Award, University of Maine, 2021
  • Nominee for Excellence in Teaching Award, Maine Business School, 2021, 2022
  • The C Oswald George Prize, The Royal Statistical Society, 2013
  • Nominee for Teacher of the Year, College of Business and Public Policy, University of Alaska Anchorage, 2012, 2013


Graham, M, & Lu, Y. (2022). Skills Expectations in Cybersecurity: Semantic Network Analysis of Job Advertisements. Journal of Computer Information Systems, Forthcoming

Lu, Y., Zheng, Q., & Quinn, D. (2022). Introducing Causal Inference Using Bayesian Networks and do-Calculus. Journal of Statistics and Data Science Education, Forthcoming

Ye, Y., Lu, Y., Robinson, P., & Narayanan, A. (2022). An empirical Bayes approach to incorporating demand intermittency and irregularity into inventory control. European Journal of Operational Research, 303, 255-272.

Lu, Y. & Zheng, Q. (2021). Twitter public sentiment dynamics on cruise tourism during the COVID-19 pandemic. Current Issues in Tourism, 24(7), 892–898. 

Lu, Y. (2019). Bayesian assessment of predictors’ contributions to variation in the predictive performance of a logistic regression model. Journal of Business Analytics, 2(2), 134–146. 

Lu, Y., & Westfall, P. H. (2019). Simple and flexible Bayesian inferences for standardized regression coefficients. Journal of Applied Statistics, 46(12), 2254–2288. 

Gonen, M., Johnson, W. O., Lu, Y., & Westfall, P. H. (2019). Comparing objective and subjective Bayes factors for the two-sample comparison: The classification theorem in action. The American Statistician, 73(1), 22-31. (This paper is selected by the Editor-in-Chief as “Editor’s Choice: Papers Appearing in 2019”.)

Zheng, Q., Wang, H. H., & Lu, Y. (2018). Consumer purchase intentions for sustainable wild salmon in the Chinese market and implications for agribusiness decisions. Sustainability, 10(5), 1377(1-16).

Jeffries, F. L., & Lu, Y. (2018). Emotional intelligence as an influence on ethical behavior: a preliminary study. Journal of Behavioral and Applied Management, 18(1), 19-32.

Zheng, Q., & Lu, Y. (2016). Do you catch undersized fish? Let’s go fishing to learn some important concepts in multiple testing. Teaching Statistics, 38(3), 91-97.

Lu, Y., Westfall, P. H., Han, G., & Bui, M. M. (2016). Bayesian hypothesis testing for selected regression coefficients. Communication in Statistics – Theory and Methods, 45(23), 7011-7026.

Jeffries, F. L., Alevy, J., & Lu, Y. (2014). Gender- and frame-specific audience effects in dictator games. Economics Letters, 122(1), 50-54.

Lu, Y., & Henning, K. S. (2013). Are statisticians cold-blooded bosses? A new perspective on the old concept of statistical population. Teaching Statistics, 35(1), 66-71.

Lu, Y., & Desai, A. (2013). Designing a business intelligence emphasis in the MBA program. The 2013 Information Systems Educators Conference Proceedings.

Lu, Y., & Zheng, Q. (2013). A simple p-value adjustment for group sequential test. The 2013 Southwest Decision Sciences Conference Proceedings.

Lu, Y., & Chen, W. (2011). Unreliable inference for business and economics event studies based on variance dummy variable in a GARCH regression model. Journal of Applied Business and Economics 12(5), 45-53.

Liu, C., & Lu, Y. (2010). Energy performance in the US electric power generation: Is renewable energy technology still as promising development and worth to pursue? The 2010 IABPAD Conference Proceedings.

Lu, Y., & Westfall, P. H. (2009). Is Bonferroni admissible for large m? American Journal of Mathematical and Management Sciences 29(1), 51-69.

Westfall, P. H., Tsai, K., Ogenstad, S., Tomoiaga, A., Moseley, S., & Lu, Y. (2008). Clinical trials simulation: A statistical approach. Journal of Biopharmaceutical Statistics 18, 611-630.

Gonen, M., Johnson, W. O., Lu, Y., & Westfall, P. H. (2005). The Bayesian two-sample t test. The American Statistician 59, 252-257.