Matthew Dixon

Assistant Professor of Statistics & Finance

Stuart School of Business

Illinois Tech
mdixon7 at stuart dot iit dot edu
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Matthew Dixon is a British Applied Mathematician working in the area of algorithmic finance. His research focuses on applying concepts in computational and applied mathematics to financial modeling, especially in the area of algorithmic trading and derivatives. Matthew's research is currently funded by Intel Corporation and he develops codes for high performance architectures. His work in deep learning with Diego Klabjan (NWU) has brought wide recognition and he is a frequently invited speaker at quant and fintech events around the world in addition to be referenced as a computational finance expert in multiple reputed media outlets including the Financial Times and Bloomberg Markets.


He has contributed to the R package repository and published around twenty peer-reviewed technical articles. Matthew's teaching style focuses on motivating abstract mathematical modeling ideas with computer experiments in Python and R. He has taught machine learning, computational finance, Bayesian econometrics and financial econometrics, and held visiting research appointments in CS/Math at Stanford University and UC Davis.


Matthew is the co-founder of the Thalesians, a quant educational company which is a member of Level39, Europe's biggest financial technology Incubator. Prior to joining academia, he has held industry appointments as a quant at banks such as Lehman Brothers, the Bank for International Settlements and Barclays Capital. From 2010-2015, he chaired the workshop on high performance computational finance at the annual SuperComputing conference and has served on the program committee of HPC. Matthew holds a MSc in Parallel and Scientific Computation (with distinction) from the University of Reading, and a PhD in Applied Math from Imperial College London. He became a chartered financial risk manager in 2014. More about my research.