Musa Caglar
- Professor of Practice
- Director of Analytics and AI Program
| Office Address | GWBC - Room 402W |
|---|---|
| Phone | (504) 247 1179 |
| mcaglar@tulane.edu | |
| CV | Download CV |
Biography
Musa Caglar is a Professor of Practice in Business Analytics and Management Science at the A. B. Freeman School of Business, Tulane University. He also serve as a Director of Analytics and AI Program at A.B. Freeman School of Business. He received 2024 Dean`s Excellence in Intellectual Contributions Award. He teaches business analytics, modeling & analytics, SQL & business intelligence, web analytics, and analytics for managers courses at the A.B. Freeman School of Business. He is also owner of the www.webanalyticsclass.com to teach web analytics at its best via experiential learning.
In addition to his academic experience, Dr. Caglar has ten years of professional experience in business analytics and evidence-based decision making, including serving as coordinator for the assessment of research centers at the Scientific and Technological Research Council of Turkey, the National Science Foundation equivalent of Turkey. In his PhD. dissertation, supervised by Prof. Sinan Gürel, motivated by the problems that exist in the practice of public R&D project portfolio management, he provides innovative implementations of analytics & operations research approaches for research councils that are aiming to integrate methodologies of data analytics, mathematical modeling & optimization including fairness concerns, and simulation for better R&D project portfolio management.
Conducting research and contributing to the literature of operations research and analytics are important to him. His research interests include application of optimization, simulation and machine learning (AI & ML) algorithms to the practical problems in public sector organizations, healthcare and finance. As an award-winning professor, his research has been published in various premier outlets (academic journals and international conferences) such as Annals of Operations Research, Information Systems Frontiers, OR Spectrum, Socio-Economic Planning Sciences, Expert Systems with Applications, Production and Operations Management (POMS) Conference, Institute for Operations Research and the Management Sciences (INFORMS) Annual Conference, International Conference on Operations Research, among others. His recent ongoing collaborative research focuses on healthcare analytics. He and his colleagues apply machine learning and optimization algorithms on real data sets to assist decision making in health policy and medical practice.
Dr. Caglar serves as an ad-hoc reviewer for journals including Annals of Operations Research, OR Spectrum, Socio-Economic Planning Sciences, Expert Systems with Applications, and International Journal of Machine Learning and Cybernetics. He also serves as a reviewer for INFORMS Workshop on Data Mining and Decision Analytics (DMDA), which is organized by Data Mining Society of INFORMS.
He earned his M.S and PhD. in Industrial Engineering (Operations Research and Management Science) at prestigious METU, Ankara, Turkey. He received his bachelor’s degree in Industrial Engineering (Operations & Supply Chain Management/Information Systems) from well-known School of Management at ITU, Istanbul, Turkey.
Courses
MGSC 3010 Intro to Business Analytics
MGSC 4590 Business Data Exploration & Visualization
MGSC 7100 SQL Data Fundamentals and Business Intelligence
MGSC 7310 Modeling and Analytics
MGSC 7340 Web Analytics
MGSC 6030 Analytics for Managers
MGSC 7340 Web Analytics
Research
- A Compartmental Model to Analyze COVID-19 Spread: Policies and Strategies to Control the Pandemic (Work-in-Process, with E. Kibis, A. Dag., S. Simsek, A. Ivanov, O. Cosgun)
- Dag, A., Asilkalkan, A., Aydas, O.T., Caglar, M., Simsek, S., Delen, D., A Parsimonious Tree Augmented Naive Bayes Model for Exploring Colorectal Cancer Survival Factors and Their Conditional Interrelations, Information Systems Frontiers, 27, 1209-1225, 2025. https://link.springer.com/journal/10796/volumes-and-issues/27-3
- Caglar, M. and Gürel, S., R&D Project Portfolio Selection Problem under Expenditure Uncertainty,Annals of Operations Research, 341, 375-399, 2024 (Special Issue: Data Science and Decision Analytics). https://link.springer.com/article/10.1007/s10479-023-05638-2
- Dolatsara, H.A., Kibis, E., Caglar, M., Simsek, S., Dag, A., Dolatsara, G.A., Delen, D., An Interpretable Decision-Support System for Daily Cryptocurrency Trading, Expert Systems with Applications,Vol. 203, p.117409, 2022. https://doi.org/10.1016/j.eswa.2022.117409
- Yucel A., Caglar, M., Dolatsara, H.A., George, B., Dag, A. Predicting Hotel Reviews from Sentiment: A Multinomial Classification Framework, Journal of Modelling in Management, Vol. 17 No. 2, pp. 697-714, 2022. https://doi.org/10.1108/JM2-09-2020-0255
- Caglar, M. and Gürel, S., Impact Assessment based Sectoral Budget Balancing in Public R&D Project Portfolio Selection Problem, Socio-Economic Planning Sciences, Vol. 66, pp. 68-81, 2019. https://doi.org/10.1016/j.seps.2018.07.001
- Caglar, M. and Gürel, S., Public R&D Project Portfolio Selection Problem with Cancellations, OR Spectrum, Vol. 39, Issue 3, pp. 659 - 687, 2017. https://link.springer.com/article/10.1007/s00291-016-0468-5
