Maximilian SCHIFFER

Professeur Associé

Information Systems et Operations Management

schiffer@hec.fr
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Biographie

Maximilian Schiffer is an Associate Professor in the Information Systems and Operations Management department at HEC Paris and holds the Hi! PARIS Chair in “Artificial Intelligence for Decision Making in Business” at HEC Paris, supported by the France 2030 AI Cluster programme. Prior to joining HEC, he was a tenured Professor at the Technical University of Munich (TUM). He received his Ph.D. in Operations Research from RWTH Aachen University in 2017 and subsequently held a visiting postdoctoral scholar position at Stanford University.

His research operates at the intersection of artificial intelligence, machine learning, and operations research. Specifically, his work focuses on Decision-Focused Learning, Structured Reinforcement Learning, and stochastic optimization, developing methodologies for high-impact business decision-making in operations, supply chains, and transportation. He regularly publishes in top-tier Operations Research and Management Science journals, including Management Science, Operations Research, Mathematical Programming, and Production and Operations Management. Additionally, his work frequently appears at leading machine learning conferences such as NeurIPS, ICML, ICLR, and AAAI.

Maximilian's contributions to the field have been recognized with numerous honors, including the INFORMS TSL Dissertation Prize , the GOR Doctoral Dissertation Prize , and the Paper of the Year 2024 Award from INFORMS Transportation Science. He is also a frequent speaker at leading international venues, having delivered among others the opening keynote at ROADEF 2025 in Paris , as well as invited keynotes at LION , the AAAI AI4Opt Workshop , and a Pierce Seminar at Massachusetts Institute of Technology

Articles scientifiques

On the benefits of ex-post pricing for ride-pooling

Transportation Research Part C: Emerging Technologies, octobre 2023, vol. 155, n° 104290, (in coll. with P. Karaenke, S. Waldherr)

Electric Vehicle Charge Scheduling with Flexible Service Operations

Transportation Science, novembre - décembre 2023, vol. 57, n° 6, pp 1605-1626, (in coll. with P. S. Klein)

Coordinated charging station search in stochastic environments: A multiagent approach

Production and Operations Management, août 2023, vol. 32, n° 8, pp 2596-2618, (in coll. with M. Guillet)

Online Routing Over Parallel Networks: Deterministic Limits and Data-driven Enhancements

INFORMS Journal on Computing, mai - juin 2023, vol. 35, n° 3, pp 560-577, (in coll. with D. Jalota, D. Paccagnan, M. Pavone)

On the integration of battery electric buses into urban bus networks

Transportation Research Part C: Emerging Technologies, juin 2022, vol. 139, n° 103628, (in coll. with N. Dirks, G. Walther)

Disruption evaluation in end-to-end semiconductor supply chains via interpretable machine learning

IFAC-PapersOnLine (formerly known as IFAC Proceedings Volumes), 2022, vol. 55, n° 10, pp 661-666, (in coll. with F.-M. Jaenichen, C. J. Liepold, A. Ismail, H. Ehm)

A Large Neighborhood Search for the Vehicle Routing Problem with Multiple Time Windows

Transportation Science, septembre - octobre 2022, vol. 56, n° 5, pp 1369-1392, (in coll. with H. Schaap, M. Schneider, G. Walther)

Optimal Picking Policies in E-Commerce Warehouses

Management Science, octobre 2022, vol. 68, n° 10, pp 7497-7517, (in coll. with N. Boysen, P. S. Klein, G. Laporte, M. Pavone)

Electric Vehicle Charging Station Search in Stochastic Environments

Transportation Science, mars - avril 2022, vol. 56, n° 2, pp 483-500, (in coll. with M. Guillet, G. Hiermann, A. Kröller)

Customer Order Behavior Classification Via Convolutional Neural Networks in the Semiconductor Industry

IEEE Transactions on Semiconductor Manufacturing, août 2022, vol. 35, n° 3, pp 470-477, (in coll. with M. Ratusny, H. Ehm)

Actes de conférence

Cahiers de recherche

Articles scientifiques

Support vector machines with the hard-margin loss: optimal training via combinatorial Benders’ cuts

Journal of Global Optimization, mai 2025, vol. 92, n° 1, pp 205-225, (in coll. with Í. Santana, B. Serrano, T. Vidal)

Bilevel optimization for feature selection in the data-driven newsvendor problem

European Journal of Operational Research, juin 2024, vol. 315, n° 2, pp 703-714, (in coll. with B. Serrano, S. Minner, T. Vidal)

Column generation for solving large scale multi-commodity flow problems for passenger transportation

European Journal of Operational Research, avril 2024, vol. 314, n° 2, pp 703-717, (in coll. with B. Lienkamp)

Combinatorial Optimization-Enriched Machine Learning to Solve the Dynamic Vehicle Routing Problem with Time Windows

Transportation Science, juillet - août 2024, vol. 58, n° 4, pp 708-725, (in coll. with L. Baty, K. Jungel, P. S. Klein, A. Parmentier)

Actes de conférence

Cahiers de recherche

Formation

  • Ph.D. (with honors) in Operations Research, RWTH Aachen University - Allemagne

Nominations académiques

Responsabilités académiques à HEC

  • 2026- Professeur Associé HEC Paris

Responsabilités académiques externes

  • 2022-2022 Professor for Business Analytics and Intelligent Systems Technical University of Munich_TUM

Activités scientifiques

Adhésion à l'organisation académique ou professionnelle

  • Membre : German Society of Operations Research (GOR), Institute for Operations Research and the Management Sciences (INFORMS), Deutscher Hochschullehrer Verband (DHV), Verband der Hochschullehrer für Betriebswirtschaftslehre (VHB)

Activités scientifiques

  • 2021- Editorial advisory board member (early career) Transportation Research Part C

    • Prix ​​& honneurs

    • 2025 Paper of the Year 2024 Award, INFORMS Transportation Science
    • 2025 Best Paper Award, LION19 – The 19th Learning and Intelligent Optimization Conference