Analytics — Business Analytics and Information Systems
Matthew   Dixon

Matthew Dixon, Ph.D.

Term Assistant Professor

Term Assistant Professor Matthew Dixon is a respected international researcher and consultant of analytics and financial risk, whose career has taken him all over the world. He has taught computational analytics, data acquisition and applications of analytics in the Master of Science in Analytics program.

Dr. Dixon began his career as a quantitative developer at Lehman Brothers in London before pursuing academics and consulting in the finance and IT industry for many years.  One of his most recent projects included consulting for the private equity firm Silver Lake to develop predictive analytics for identifying investment opportunities. He holds a Ph.D. in Applied Mathematics from the Imperial College in London, and his research focuses on the application of numerical algorithms to compute-intensive and large-scale analytics, especially for financial risk and sustainable infrastructure design.

Dr. Dixon was born and raised in the United Kingdom, and holds a Master of Science in Parallel and Scientific Computation from the University of Reading, and a Master of Engineering and Ph.D. in Applied Mathematics from the Imperial College of London. He relocated to California in 2007, believing the Bay Area to be unparalleled in the opportunities it offers professionals in the technical world. He has owned his own quantitative analytics consultancy in Silicon Valley since 2011, and consults for organizations and business leaders all across the U.S. 


M.Eng., Civil and Environmental Engineering, Imperial College, London, United Kingdom, 1999
M.Sc., Parallel and Scientific Computation (with distinction), University of Reading, United Kingdom, 2002
Ph.D., Applied Mathematics, Imperial College, London, United Kingdom, 2007
Postdoctoral work, Institute for Computational and Mathematical Engineering, Stanford University, 2007 – 2008

Courses Offered
  • MSAN 605: Practicum I
  • MSAN 692: Data Acquisition

The following list is a selection of recent publications and does not represent the entire body of research.

“Accelerating Value-at-Risk Estimation on Many-Core and Multi-Core Architectures,” (with co-authors J. Chong and K. Keutzer) The Journal of Concurrency and Computation: Practice and Experience, Vol. 24, No. 8, Wiley, 2011

“Monte Carlo Based Financial Market Value-at-Risk Estimation on GPUs,” (with co-authors T. Bradley, J. Chong and K. Keutzer) chapter 25 in GPU Computing Gems, Jade Edition, Wen-Mei Hwu and Morgan Kaufmann (Eds.), 2011

“Enabling Technology for more Pervasive and Responsive Market Risk Management Systems,” (with co-authors J. Chong and K. Keutzer) chapter in The Risk of Investment Products, Michael Wong (Ed.), World Scientific Press, 2011

“Error Control of Iterative Linear Solvers for Integrated Groundwater Models,” (with co-authors Z. Bai, C.F. Brush, F.I. Chung, E.C. Dogrul and T.N. Kadir) Groundwater, Vol. 49, No. 6, 2011

Honors and Awards

UK GET Award for Research in Applied Mathematics, 2004 & 2005

1st prize, Department of Mathematics Postgraduate Poster Competition, Imperial College, London, U.K., 2004 & 2007

Institution of Civil Engineers Queen’s Jubilee Scholarship, 1995-1999


Owner, Quiota LLC, a quantitative analytics consulting company, Silicon Valley, CA, 2011 – present

Arthur Krener Assistant Professor in Applied Mathematics, University of California at Davis, Department of Mathematics, 2010 – 2011

Chair of the Workshop on High Performance Computational Finance, SuperComputing.

Founder of the Thalesians, a quantitative finance and analytics educational company hosting seminars in New York and London

Organization Committee, Global Association of Risk Professionals (GARP), San Francisco chapter

Matthew Dixon, University of San Francisco School of Management