Jye-Chyi Lu

Professor

Contact

 Groseclose 333
 404.894.2318
 Personal website
 Curriculum Vitae
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Education

  • Ph.D. Statistics (1988), University of Wisconsin
  • B.S. Applied Mathematics (1979), National Chiao-Tung University, Taiwan

Expertise

  • Data Mining
  • Industrial Statistics
  • Quality and Reliability Engineering
  • Supply Chain and Logistics

About

Jye-Chyi (JC) Lu is a professor in in the Stewart School of Industrial and Systems Engineering (ISyE) at Georgia Tech (GT).

Dr. Lu is active in promoting research, education and extension-service programs with focus on engineering statistics and analytics areas. Dr. Lu received a Ph.D. in statistics from University of Wisconsin at Madison in 1988, and joined the statistics faculty of North Carolina State University, where he remained until 1999 when he joined GT-ISyE. He has 100 journal publications in engineering and statistics journals. Twenty-seven Ph.D. students have graduated under his supervision.  His research has been supported by many NSF awards and industry grants. He serves as an associate editor (AE) for the Journal of Quality Technology and had served as AEs for Technometrics and IEEE Transactions on Reliability.  He is a Fellow in the American Statistical Association, and has been INFORMS Quality, Statistics and Reliability section chair.

Research

My research partner, Professor Tsao, in Taiwan, has two major grants funded by the Taiwanese National Science and Technology Council, where I cannot serve as a co-PI, but as the lead foreign collaborator. One grant (19-24; $935,867) involves applying economic decision modeling/optimization and data-driven analytic tools to solve energy distribution network design problems. The other grant (24-27; $483,335) works on “Intelligent Operations and Optimization Problems for New Generational Grid Edge Ecosystem”. We have a few Ph.D. students in Taiwan working in research areas identified in the above grants. In 2024, we have five articles accepted or published and four new manuscripts submitted for reviews. 

Teaching

I have taught seven courses in 2024 with a total of 326 UG, MS and Ph.D. students. The sizes of my regular semester classes are large (e.g., 65, 74 and 86 students). The weighted average CIOS teaching effectiveness score is 4.535 from all classes. The high CIOS evaluations 4.79 (from ISyE 7406) and 4.82 (from ISyE 4034-A) in the Fall courses, where ISyE 4034-A got into CIOS Honor Roll. I have devoted a considerable amount of time to coaching 10+ teams in each semester for guiding students project studies. I have also developed step-by-step instructional guides for teaching students how to use Microsoft Azure and Google AutoML to compare their performance and usability against the traditional data analytics tools in R and Python. Moreover, I have worked with student teams to synthesize popular AI tools with case studies in their semester project studies.

Awards and Honors

  • 2021 Summer, 2022 Summer, 2023 Spring, 2023 Summer, 2024 Fall, 2025 Spring and 2025 Summer CIOS Honor Rolls.
  • Student Recognition of Excellence in Teaching: 2022 CIOS Award.
  • Jim Pop Fellowship
  • INFORMS QSR (Quality, Statistics and Reliability) Cluster-Chair 2007
  • Fellow ASA, August 2007
  • INFORMS QSR (Quality, Statistics and Reliability) Program-Chair 2006
  • IEEE Senior Member 2003
  • North Carolina State University Outstanding Extension Service Award 1997 - 1998
  • NCSU PAMS College Outstanding Faculty Outreach Award 1996 - 1997
  • David D. Mason Outstanding Faculty Award in the Department of Statistics, NCSU 1996

Representative Publications

  1. Lu, J.-C. and Bhattacharyya, G. K. (1990), “Some New Constructions of Bivariate Weibull Models,” Annals of the Institute of Statistical Mathematics, 42, 3, 543-559.
  2. Lu, J.-C. and Bhattacharyya, G. K. (1991), “Inference Procedures for a Bivariate Exponential Model of Gumbel Based on Life Test of System and Components,” Journal of Statistical Planning and Inference, 27, 383-396.
  3. Mesenbrink, P., Lu, J.-C., McKenzie, R., and Taheri, J. (1994), “Characterization and Optimization of A Wave Soldering Process,” Journal of the American Statistical Association, 89, 1209-1217.
  4. Lu, J.-C., Park, J. and Yang, Q. (1997), “Statistical Inference of a Time-to-Failure Distribution from Linear Degradation Data,” Technometrics, 39(4), 391-400.
  5. Hughes-Oliver, J. M., Lu, J.-C., Davis, J. C., and Gyurcsik, R. S. (1998), “Achieving Uniformity in a Semiconductor Fabrication Process Using Spatial Modeling,” Journal of the American Statistical Association, 93, 36-45.
  6. Lu, J.-C., Holton, W. C., Fenner, J. S., Williams, S. C., Kim, K. W., Hartford, A. H., Chen, D., Roze, K., and Littlejohn, M. A. (1998), “A New Device Design Methodology,” IEEE Transactions on Electron Devices - Special Issue on Process Integration and Manufacturability, 45(3), 634-642.
  7. Li, C. S., Lu, J.-C., Park, J., Kim, K. M., Brinkley, P. A., and Peterson, J. (1999), “A Multivariate Zero-Inflated Poisson Distribution and Its Inferences,” Technometrics, 41(1), 29-38.
  8. Chen, D., Lu, J.-C., X. Huo, and Ming, Y. (2001), “Robust Estimation with Estimating Equations for Nonlinear Random Coefficients Model,” Journal of Statistical Planning and Inference, 37, 275-292.
  9. Lada, E. K., Lu, J.-C., and Wilson, J. R. (2002), “A Wavelet Based Procedure for Process Fault Detection,” IEEE Trans. on Semiconductor Manufacturing, 15(1), 79-90.
  10. Rying, E. A., Bilbro, G. L., and Lu, J.-C. (2003), “Focused Local Learning with Wavelet Neural Networks,” IEEE Trans. on Neural Network, 13(2), 304-319.
  11. Fenner, J. S., Jeong, M. K., and Lu, J.-C. (2005) (author names are in an alphabetical order), “Optimal Automatic Control of Multi-Stage Production Processes,” IEEE Trans. on Semiconductor Manufacturing, 18(1), 94-103.
  12. Lu, J.-C., Chen, D., and Zhou, W. (2006), “Generalized Linear Models with Random Scales and Integrated Extended Quasi-Likelihood Estimates,” Journal of Statistical Planning and Inference, 136(2), 401-429.
  13. Jeong, M. K., Lu, J.-C., Huo, X., Vidakovic, B., and Chen, D. (2006), “Wavelet-based Data Reduction Techniques for Process Fault Detection,” Technometrics, 481(1), 26-40.
  14. Wang, N., Kvam, P., and Lu, J.-C. (2007), “Detection and Estimation of A Mixture in A Power Law Process for A Repairable System,” Journal of Quality Technology, 39(2), 140-150.
  15. Lin, S.-C., Kvam, P., and Lu, J.-C. (2009), “Extending the Skill Test for Disease Diagnosis,” Statistics in Medicine, 28(5), 798-813.
  16. Fenner, J. S., Jeong, Y.-S., Jeong, M.K., and Lu, J.-C. (2009), “Bayesian Parallel Site Model with An Application to Uniformity Monitoring in the Semiconductor Manufacturing,” IIE Transactions, 41(9), 754-763.
  17. Wang, N., Lu, J.-C., Kvam, P., and Chen, D. (2011), “Adjusted Empirical Likelihood Models with Estimating Equations for Accelerated Life Tests,” Journal of Statistical Planning and Inference, 141(1), 140-155.
  18. Irion. J., Lu, J.-C., Al-Khayyal, F. A., and Tsao, Y.-C. (2011), “A Hierarchical Decomposition Approach to Retail Shelf Space Management and Assortment Decisions,” Journal of Operations Research Society, 62, 1861-1870.
  19. Kim. H., Lu, J.-C., Kvam, P. H., and Tsao, Y.-C. (2011), “Ordering Quantity Decisions Considering Uncertainty in Supply-Chain Logistics Operations”, International Journal of Production Economics, 134(1), 16-27.
  20. Tsao, Y.-C., and Lu, J.-C. (2012), “A Supply Chain Network Design Considering Transportation Cost Discounts”, Transportation Research Part E: Logistics and Transportation Review, 48(2), 401-414.
  21. Lu, J.-C., Tsao, Y.-C., and Charoensiriwath, C. (2012), “Dynamic Decision-Making in A Two-stage Supply Chain with Repeated Transactions, International Journal of Production Economics, 137(2): 211-225.
  22. Irion, J., Al-Khayyal, F. A., Lu, J.-C., and Tsao, Y.-C. (author names are in an alphabetical order) (2012), “A Piecewise Linearization Framework for Retail Shelf Management Models,” European Journal of Operations Research, 222(1): 122-136.
  23. Tsao, Y.-C., Mangotra D., Lu J.-C., and Dong, M. (2012), “A Continuous Approximation Approach for the Integrated Facility Location-Inventory Allocation Problem,” European Journal of Operational Research, 222(2), 216-228.
  24. Vastola, J. T., Lu, J.-C., Casciato, M. J., Hess, D. W., and Grover, M. A. (2013), “A Framework for Initial Experimental Design in the Presence of Competing Prior Knowledge,” Journal of Quality Technology, 45(4), 301-329.
  25. Kim, S., Kim, H., Lu, J.-C., Casciato, M. J., Grover, M. A., Hess, D. W., Lu, R. W., and Wang, X. (2015), “Layers of Experiments with Adaptive Combined Design,” Naval Research Logistics, 62(2), 127-142.
  26. Vastola, J. T., Kim, H., Kim, S., Lu, J.-C., and Grover, M. A. (2017), “Batch Sequential Minimum Energy Design with Design Region Adaptation”, Journal of Quality Technology, 49(1), 11-26.
  27. Jeong, Y.-S., Jeong, M.-K., Lu, J.-C., Yuan, M., and Jin, J. (2018), “Statistical Process Control Procedures for Functional Data with Systematic Local Variations”, IIE Transactions, 50(5), 448-462.
  28. Tsao, Y.-C., Thanh, V.-V., and Lu, J.-C. (2019), “A Multi-Objective Robust Fuzzy Stochastic Approach for Sustainable Smart Grids Design”, Energy, 176, 929-939.
  29. Tsao, Y.-C., Thanh, V.-V., and Lu, J.-C. (2021), “Sustainable advanced distribution management system design considering differential pricing schemes and carbon emissions”, Energy, 219: 119596.
  30. Tsao, Y.-C., Thanh, V.-V., Lu, J.-C. (2022), “Efficiency of Resilient Three-Part Tariff Pricing Schemes in Residential Power Markets”, Energy, 239: 122329.
  31. Tsao Y. C., Ho A. I., Lu J.-C., Wang C. (2024), “Game Theory-Based Electricity Pricing Decisions Incorporating Prosumer Energy Preferences and Renewable Portfolio Standard”, Energy, 306: 132418.
  32. Yang, S.-T., Lu, J.-C., Tsao, Y.-C. (2025), “Clustering and Representative Selection for High-Dimensional Data with Human-in-the-Loop”, INFORMS Journal of Data Science, 4(2), 154-172.

Note: Names with bold faces were my students.