Mihalis G.
Markakis

Associate Professor of Operations, Information and Technology

• Ph.D, Massachusetts Institute of Technology
• M.Sc, University of Southern California
• B.Sc, National Technical University of Athens

Mihalis holds a PhD in Engineering from the Massachusetts Institute of Technology. His research lies in the intersection of operations and revenue management; combines concepts and methodologies from Operations Research, Economics, and Machine Learning; and aims to solve problems in urban mobility, transportation, logistics and global supply chains. His work has been published in top academic journals, such as Management Science, Manufacturing & Service Operations Management, Transportation Research, and Mathematics of Operations Research. He serves in the editorial board of Manufacturing & Service Operations Management.

At IESE, Mihalis teaches courses on Operations Management, Operations Strategy, and Pricing and Revenue Management at the school’s MBA, Executive MBA, and Executive Education programs. He has held teaching positions at the London Business School, the Sloan School of Management, and INSEAD, as well as a research intern position at Bell Labs. He is the recipient of the Ramón y Cajal and the Juan de la Cierva fellowships from the Spanish government, as well as of the Leonardo fellowship from the BBVA Foundation.

Curriculum Vitae

Areas of interest.

• Pricing and Revenue Management
• Transportation and Logistics
• Supply Chain Management

Publications

Journal Articles (refereed)

LUGOSI, G., MARKAKIS, M. G., NEU, G. (2024). On the hardness of learning from censored and nonstationary demand. INFORMS Journal on Optimization, 6 (2), 63–83. doi:10.1287/ijoo.2022.0017. MARKAKIS, M., TALLURI, K., TIKHONENKO, D. (2023). Sequential bidding for merging in algorithmic traffic. Manufacturing & Service Operations Management, 25 (1), 168-181. doi:10.1287/msom.2022.1144. MARKAKIS, M., TALLURI, K., TIKHONENKO, D. (2022). Managing lane-changing of algorithm-assisted drivers. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 138, article 103586. doi:10.1016/j.trc.2022.103586.

Working Papers

MARKAKIS, M. G., MARTÍNEZ DE ALBÉNIZ, V., SERRANO, M. (2024). Bayesian demand learning and revenue management under limited capacity. SSRN Electronic Journal. MARKAKIS, M. G., MARTÍNEZ DE ALBÉNIZ, V., BARRIOLA, X., SÁNCHEZ, C. (2023). Building and maintaining an assortment of durable goods. SSRN Electronic Journal.

Studies

MARTÍNEZ DE ALBÉNIZ, V., ECHAVE MARTÍNEZ, C. (2020). Big Data at the service of social inclusion.

Cases

VALENTÍ, A., MARKAKIS, M. G., GARITANO, T. (2025). EcoMetrics: qué precio ponerle a la medición de la publicidad sostenible. IESE, M-1420. VALENTÍ, A., MARKAKIS, M. G., GARITANO, T. (2025). EcoMetrics: How to price the measurement of sustainable advertising? IESE, M-1420-E. MARKAKIS, M. G., TALLURI, K., MUGE TEKIN (2024). Collegeville Hotels: Putting competitive intelligence data to use. IESE, OIT-42-E.

Projects with external financing

• “Data-driven competitive advantage: the information edge in operations management,” co-PI Victor Martínez de Albéniz (2021-2024). Grant: PID2020-116135GB-I00 funded by:

 

• “Information processing and resource allocation in online markets and networks,” sole PI. (2016-2019).  Grant: ECO2016-75905-R funded by:

 

• “Smart-pricing solutions to relieve traffic congestion, exploiting new inter-vehicular communication,” co-PI Kalyan Talluri (2014-2016). Grant:  ECO2013-41131-R funded by Spanish Ministry of Economy and Competitiveness.

 

• “Licitación de posición dinámica para el tráfico algorítmico.” Leonardo Fellowship (2021-2022), funded by BBVA Foundation 2021-2022

 

• Ramón y Cajal Fellowship (2019-2023). Grant: RYC-2017-23656 funded by:

 

• Juan de la Cierva Fellowship (2017-2018). Grant: IJCI-2015-26417  funded by:

 

• COFUND Fellowship, Marie Curie Actions, European Commission 2013-2016