Martin Haugh

Martin Haugh is an Associate Professor of Analytics and Operations Research at Imperial College Business School. He holds a PhD in Operations Research from MIT and MSc degrees in Mathematics and Applied Statistics. His research focuses on computational finance, stochastic control, and data science applications in sports analytics and causal inference.

His educational background includes:

• PhD in Operations Research - Massachusetts Institute of Technology
• MSc in Applied Statistics - University of Oxford
• MSc in Mathematics - University College Cork

Research interests span three primary domains:

1. Quantitative Finance: Portfolio optimization with taxes, derivatives pricing, and risk management using deep learning approaches
2. Stochastic Control: Information relaxation techniques for bounding optimal value functions in complex decision processes
3. Data Analytics: Sports performance modeling, causal inference in healthcare, and political election analysis

His recent publications (2015-2024) demonstrate a consistent focus on applied mathematical modeling across finance, economics, and competitive strategy domains, with emerging emphasis on counterfactual analysis and machine learning applications.

He serves as Associate Editor for Management Science and INFORMS Journal on Computing, and mentors graduate students in the MSc Business Analytics program.