Part-Time Lecturer
Education
- B.S. Chemical Engineering (1989), Pontificia Universidade Catolica do Rio Grande do Sul
- M.S. Industrial Engineering (1994), Universidade Federal do Rio Grande do Sul
- Ph.D. Industrial & Systems Engineering (1997), Rutgers - The State University of New Jersey
Expertise
- Health and Humanitarian Systems
- Analytics and Machine Learning
- Data Science and Statistics
About
Flavio S. Fogliatto is a Part-Time Lecturer in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology. He also serves as an Adjunct Professor in the Ph.D. Program in Industrial Engineering at the Federal University of Rio Grande do Sul. He is currently an appointed member of the Industrial Engineering Advisory Committee of the National Council for Scientific and Technological Development (CNPq), Brazil.
Research
Dr. Fogliatto's research applies industrial engineering, operations management, and advanced analytics to healthcare systems, quality engineering, and resilient operations. His work integrates statistical modeling, machine learning, and lean methodologies to improve the efficiency, reliability, and resilience of complex service and manufacturing systems. Recent research focuses on healthcare operations in digitally enabled environments, including the optimization of surgical center operations and measuring the resilience of individuals and teams in healthcare. He also contributes to quality engineering and multivariate statistical methods, including early influential work on mass customization. Dr. Fogliatto collaborates internationally with partners at Macquarie University, Sapienza University of Rome, University of Melbourne, and institutions in France, the UK, Chile, and Canada.
Awards and Honors
- Best Doctoral Paper Award, XI Brazilian Meeting on Research and Graduate Studies in Industrial Engineering (ANPEPRO Conference)
- Research in Engineering Lifetime Achievement Award, Rio Grande do Sul Science Foundation, Brazil
- Best Conference Paper Award, IEEE International Conference on Industrial Engineering and Engineering Management, Singapore
- IIE Transactions Best Paper Award, Institute of Industrial Engineers
Representative Publications
*Calegari, R., Fogliatto, F. S., Lucini, F. R., Brito, J. B. G., Yamashita, G. H., Anzanello, M. J., Tortorella, G. L., & Schaan, B. D. (2025). Designing a long-term master surgical timetable: A case study in balancing post-operative ward bed demand and minimizing changes in surgical schedules. Journal of Scheduling. https://doi.org/10.1007/s10951-025-00851-2
*Melo, I. E. S., & Fogliatto, F. S. (2025). Integration of decision levels in operating room scheduling problems: Systematic review and proposition of a decision support framework. Computers and Operations Research, 175, 107063. https://doi.org/10.1016/j.cor.2025.107063
*Deina, C., Fogliatto, F. S., Silveira, G. J. C., & Anzanello, M. J. (2024). Decision analysis framework for predicting no-shows to appointments using machine learning algorithms. BMC Health Services Research, 24, 37. https://doi.org/10.1186/s12913-023-10418-6
Fogliatto, F. S., Saurin, T. A., Tortorella, G. L., Dora, J. M., & Tonetto, L. M. (2024). Workspace layout for resilient performance using social network analysis: A case study. HERD: Health Environments Research & Design Journal. https://doi.org/10.1177/19375867241271435
Patriarca, R., Simone, F., Artime, O., Saurin, T. A., & Fogliatto, F. S. (2024). On the conceptualization of a functional random walker for the analysis of socio-technical systems. Reliability Engineering & System Safety, 251, 110341. https://doi.org/10.1016/j.ress.2024.110341
*Medeiros, N. B., Fogliatto, F. S., Rocha, M. K., & Tortorella, G. L. (2023). Predicting the length-of-stay of pediatric patients using machine learning algorithms. International Journal of Production Research, 63(2), 483–496. https://doi.org/10.1080/00207543.2023.2235029
*Santos, B. M., Fogliatto, F. S., Saurin, T. A., & Tortorella, G. L. (2023). Modeling help chains in health services as social networks: Moving from linearity to complexity. International Journal of Production Research. https://doi.org/10.1080/00207543.2023.2298486
Terra, S. X., Saurin, T. A., Fogliatto, F. S., & Magalhaes, A. M. M. (2023). Burnout and network centrality as proxies for assessing the human cost of resilient performance. Applied Ergonomics, 108, 103955. https://doi.org/10.1016/j.apergo.2022.103955
*Tortorella, G. L., Fogliatto, F. S., Mendoza, D. T., Pepper, M., & Capurro, D. (2023). Digital transformation of health services: A value stream-oriented approach. International Journal of Production Research, 61(6), 1814–1828. https://doi.org/10.1080/00207543.2022.2048115
*Tortorella, G. L., Prashar, A., Samson, D., Kurnia, S., Fogliatto, F. S., Capurro, D., & Antony, J. (2023). Resilience development and digitalization of the healthcare supply chain: An exploratory study in emerging economies. International Journal of Logistics Management, 34(1), 130–163. https://doi.org/10.1108/IJLM-09-2021-0438
Bertoni, V. B., Saurin, T. A., & Fogliatto, F. S. (2022). How to identify key players that contribute to resilience performance: A social network analysis perspective. Safety Science, 147, 105648. https://doi.org/10.1016/j.ssci.2021.105648
Yamashita, G. H., Anzanello, M. J., Rocha, M. K., Soares, F., & Fogliatto, F. S. (2022). Selecting relevant wavelength intervals for PLS calibration based on absorbance interquartile ranges. Chemometrics and Intelligent Laboratory Systems, 231, 104689. https://doi.org/10.1016/j.chemolab.2022.104689
Yamashita, G. H., Fogliatto, F. S., Anzanello, M. J., & Tortorella, G. L. (2022). Customized prediction of attendance to soccer matches based on symbolic regression and genetic programming. Expert Systems with Applications, 187, 115912. https://doi.org/10.1016/j.eswa.2021.115912
*Denotes co-author who is a current and/or former undergraduate or graduate research student