About Me

I am an Associate Professor of Analytics and Operations Research at Imperial College Business School (ICBS) where I have been since September 2017. I am also the Academic Director of the MSc in Business Analytics at ICBS. Prior to joining Imperial I spent more than 10 years in the Department of IE & OR at Columbia University as well as 4 years working as a quant in the hedge fund industry in New York and London. I have a Ph.D. in Operations Research from MIT and MSc degrees in Applied Statistics and Mathematics from the University of Oxford and University College Cork, respectively.

Research

My main research interests are in the areas of:

1. Quantitative finance and risk management
   Recently I’ve been working on problems related to portfolio optimization with taxes as well using deep learning in risk managment. I’ve also done some work on derivatives pricing (American, swing and leveraged ETF options) and dynamic portfolio optimization.
2. Dynamic programing and stochastic control
   I’ve mainly been working on the problems related to information relaxations. These ideas allow for the construction of tight lower and upper bounds on the optimal value functions of problems where it is too difficult to compute the optimal value function and policy exactly.
3. Data analytics
   I’ve been working in the area of sports analytics and causal inference recently. I’ve also begun working on some problems related to politics and elections.

My research papers can be found here.

Teaching

At Imperial I’ve been teaching Decision Analytics for the full-time and part-time MBA programs and several courses (Foundations of Maths & Statistics, Advanced Machine Learning, Financial Analytics) for the MSc in Business Analytics. In spring 2023 I co-taught an MRes / PhD course on Machine Learning while in spring 2024 I taught an MRes / PhD course on Stochastic Processes.

All of my teaching at Columbia was at the graduate level and mainly focussed on various courses for the MSc degrees in Financial Engineering and Operations Research. Lecture notes and slides for these courses are available here. In spring 2013 I co-taught with Garud Iyengar one of the first three MOOCs, i.e. massive open online courses, to be offered by Columbia University. The course was called Financial Engineering and Risk Management and was cited by Business Insider as one of the best free online business courses. (It also featured an interview with Emanuel Derman.) The course is no longer available but is now used in a suite of courses that together comprise a specialisation in Financial Engineering and Risk Management.

I also recently finished writing a tutorial on MCMC and Bayesian Modeling. This tutorial grew out of some lecture notes I wrote a while back for courses on Monte-Carlo Simulation and Machine Learning. The tutorial is available here.

External Service

I am an Associate Editor (AE) for Management Science (Finance department) and INFORMS Journal on Computing (Stochastic Models and Reinforcement Learning department). I was previously an AE for the Stochastics department at Management Science and the Financial Engineering department at Operations Research.

Contact Information

Martin Haugh
Department of Analytics, Marketing & Operations
Imperial College Business School
South Kensington Campus
London SW7 2AZ
United Kingdom
Email: m.haugh@ic.ac.uk