JAMMELI Haïfa
Assistant Professor
Assistant Professor
Title : Assistant Professor
Département : Management & Strategy
Biography : Holder of a Ph.D. in Management Information Systems (Institut Supérieur de Gestion de Tunis, 2021) and specialized in operations research and artificial intelligence, Haïfa JAMMELI develops a dual scientific and industrial expertise at the crossroads of advanced quantitative methods and their application to organizations' real-world challenges.
Passionate about the transformative power of algorithms and optimization on complex systems, she devotes her research to a fundamental question: how can artificial intelligence help organizations make better decisions, faster, under conditions of uncertainty? This conviction guides both her research work and her teaching approach.
Her research program is organized around three complementary strands: multi-objective optimization of sustainable urban logistics systems (stochastic VRP, two-tier distribution, smart cities), privacy-preserving machine learning (federated learning, fraud detection, financial analytics), and behavioral and organizational analysis using AI methods (dropout prediction, algorithm aversion, AI governance). Her work has been published in Annals of Operations Research, IEEE Transactions on Engineering Management, and Operational Research, and has been carried out in collaboration with local authorities, transport operators, and international academic partners (France, Hungary, Tunisia, Bahrain).
She is also the founder of Solivya Consulting, a firm specializing in operational optimization and data analytics, where she supports organizations in their digital transformation and the implementation of actionable AI solutions. Her six years of experience in industrial R&D at Normasys (Paris) enabled her to lead high-impact projects on real urban networks.
Her teaching approach is grounded in learning through real data, solving concrete problems, and hands-on managerial simulations. At NEOMA Business School, where she teaches entirely in English to international cohorts, as well as at Université Paris Nanterre and FERRANDI Paris (Supply Chain Management and Logistics), she trains decision-makers who are able to understand, evaluate, and deploy AI solutions in real professional contexts — not merely be subject to them.
Her dual grounding in scientific rigor and industry experience gives her a 360° view of AI applied to business, at the intersection of academic excellence, pedagogical innovation, and the operational demands of the market.
Publications :
Articles in peer-reviewed international journals
[J1] Jammeli, H., & Verny, J. (2025). A multi-objective model for two-level distribution system in the city of Paris. Annals of Operations Research. ABS 3 · FNEGE 3 · doi:10.1007/s10479-025-06844-w
[J2] Alaya, H., Jammeli, H., Ben Abdelaziz, F., Masmoudi, M., & Verny, J. (2024). A multi-objective transportation model for COVID-19 patients: lesson learned from France. International Transactions in Operational Research, 32(4), 2139–2158. ABS 2 · doi:10.1111/itor.13447
[J3] Jammeli, H., Ksantini, R., Ben Abdelaziz, F., & Masri, H. (2021). Sequential Artificial Intelligence Models to Forecast Urban Solid Waste in the City of Sousse. IEEE Transactions on Engineering Management, 70(5), 1912–1922. ABS 3 · doi:10.1109/TEM.2021.3081609
[J4] Jammeli, H., Argoubi, M., & Masri, H. (2021). A bi-objective stochastic programming model for the household waste collection and transportation problem. Operational Research, 21(3), 1613–1639. ABS 2 · FNEGE 3 · doi:10.1007/s12351-019-00538-5
[J5] Argoubi, M., Jammeli, H., & Masri, H. (2020). The intellectual structure of the waste management field. Annals of Operations Research, 294, 655–676. ABS 3 · FNEGE 3 · doi:10.1007/s10479-020-03570-3
Book chapter
[B1] Alaya, H., Youssef, M., & Jammeli, H. (2024). Deep Learning for Stock and Cryptocurrency Returns Prediction: A Survey. In: Forging Bridges between AI and Operations Research — Applications in Healthcare and Supply Chain Management. Springer.