معرفی
Jean Pauphilet is an Assistant Professor of Management Science and Operations at London Business School. His research develops data analytics methods for positive-impact applications, with methodological work focusing on prediction-based decision-making through new algorithms for machine learning, large-scale optimization, and optimization under uncertainty. He collaborates with medical institutions, NGOs, and companies to improve hospital operations and reduce ocean plastic pollution using analytics.
Dr. Pauphilet holds a PhD in Operations Research from the Massachusetts Institute of Technology (MIT) and an MSc (Diplome d'ingenieur) in Applied Mathematics from Ecole Polytechnique (Paris), where he is part of the French Corps des Mines. Prior to joining London Business School, he worked as an analyst for the French venture capital fund, Ventech, and has consulted for various companies on analytics strategies in energy, IT, and healthcare sectors.
His research interests center around four main directions: Algorithms for discrete and robust optimization; Optimization for machine learning and statistics; Analytics for healthcare operations; and Analytics for sustainable operations. He focuses on bridging theoretical advances in optimization with practical applications addressing real-world problems in healthcare management and environmental sustainability, particularly hospital operations and ocean plastic pollution reduction.
His publication record shows a consistent trajectory of applying advanced optimization techniques to high-impact problems. Recent work demonstrates significant theoretical contributions to low-rank optimization, sparse PCA, and robust optimization frameworks, alongside practical implementations in hospital operations and environmental sustainability. His research combines mathematical rigor with real-world applicability, often collaborating with industry partners to deploy analytics solutions.
Dr. Pauphilet has received numerous prestigious awards for his research:
- Winner of the 2024 INFORMS Data Mining and Decision Analytics Workshop Best Theoretical Paper
- Finalist for the 2025 INFORMS Innovative Applications in Analytics Award
- Winner of the 2024 POMS College of Sustainable Operations Student Paper Competition (for student Baizhi Song)
- Winner of the 2022 POMS College of Healthcare Operations Management Best Paper Competition
- Winner of the 2020 INFORMS George E. Nicholson Student Paper Competition
- Winner of the 2019 INFORMS Computing Society Student Paper Award
- Honorable Mention at the 2020 INFORMS George B. Dantzig Dissertation Award
Dr. Pauphilet actively mentors students who have achieved significant recognition, including Baizhi Song, Irra Na, and Kimberley Villalobos Carballo. His research is supported through collaborations with Hartford HealthCare, The Ocean Cleanup, and various medical institutions. He has successfully translated theoretical work into practical applications, particularly in hospital operations optimization, demonstrating the real-world impact of his research.
Dr. Pauphilet is involved with Analytics for a Better World, an initiative applying analytics to social and environmental challenges. He has developed computational tools including the SubsetSelection.jl package, a Julia implementation for computing sparse L2-regularized estimators with explicit cardinality constraints, which has gained recognition in the academic community.
