Jean Pauphilet

Assistant Professor of Management Science and Operations

MSc (Ecole Polytechnique) PhD (MIT)

Joining LBS after completing a PhD in Operations Research at Massachusetts Institute of Technology, Dr Pauphilet’s research involves collaborations with hospitals and medical institutions in the US and Europe – with a focus on analytics for healthcare operations and prediction-based decision making. He also conducts methodological work on algorithms for machine-learning, large-scale optimization, and optimization under uncertainty. His work has been published in the likes of Mathematical Programming and Statistical Science. Dr Pauphilet has also advised and consulted for various companies on their analytics strategies in the energy, IT and insurance sectors, alongside having worked as an analyst for the French venture capital fund, Ventech.

  • Healthcare operations
  • Machine learning
  • Discrete optimisation
  • Optimisation under uncertainty


Direct optimization across computer generated reaction networks balances materials use and feasibility of synthesis plans for molecule libraries

Gao H; Pauphilet J; Struble T; Coley C; Jensen K F

Journal of Chemical Information and Modeling 2021 Vol 61:1 p 493-504

From predictions to prescriptions: A data-driven response to COVID-19

Bertsimas D; et al.

Health Care Management Science 2021 Online first

Predicting inpatient flow at a major hospital using interpretable analytics

Bertsimas D; Pauphilet J; Stevens J; Tandon M

Manufacturing & Service Operations Management 2021 Online first

Probabilistic Guarantees in Robust Optimization

Bertsimas D; den Hertog D; Pauphilet J

SIAM Journal on Optimization 2021 Vol 31:4 p 2893-2920


Certifiably optimal sparse inverse covariance estimation

Bertsimas D; Lamperski J; Pauphilet J

Mathematical Programming 2020 Vol 184 p 491-530

Sparse regression: scalable algorithms and empirical performance

Bertsimas D; Pauphilet J; Van Parys B

Statistical Science 2020 Vol 35:4 p 555-578

Teaching portfolio

Our teaching offering is updated annually. Faculty and programme material are subject to change.