Dr. Matthew Dixon is a technical co-founder and CRO of CFX Labs. He is an expert quant and data scientist with extensive experience working for financial institutions such as structured credit trading for Lehman Brothers and consulted for several financial institutions including the Bank of International Settlements in Basel, Silverlake investments, and Brookfield Investments.
He holds a PhD in Mathematics from Imperial College, London, and has held a postdoctoral position at the Institute for Computational and Mathematical Engineering, Stanford University, where he conducted Department of Defense-funded research on simulating the mechanical properties of new bullet-absorbing gels for lightweight infantry armor from September 2007 to December 2008. After that, Dixon held an Arthur Krener Visiting Professorship at UC Davis where he worked on Department of Energy funded research on cooling systems for nuclear reactors.
Matthew is the recipient of Risk Magazine’s 2022 Buyside Quant of the year Award for innovative research in the development of new machine learning algorithms for wealth management. He has published 50+ articles relating to risk management and machine learning in finance & blockchain, including a highly rated textbook. His research has been featured in the Financial Times, Bloomberg Markets, and Barron's Advisor, and has received research funding from Intel, Dell, NASA JPL, and the National Science Foundation. He is a Chartered Financial Risk Manager (FRM) and serves on the board of the CFA NYC Quant Trading Committee, the World Scientific Annual Review of Fintech and the AIMS Journal of Dynamics & Games.
Matthew is passionate about software and has supported numerous open-source software initiatives including serving as a Google Summer of Code Mentor for the R Statistical Computing Project (2017) and the Chair of the IEEE/ACM Workshop on High-Performance Computational Finance (2010-2015).