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
- 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,
UK GET Award for Research in Applied
Mathematics, 2004 & 2005
1st prize, Department of Mathematics
Postgraduate Poster Competition, Imperial College, London, U.K., 2004 &
Institution of Civil Engineers Queen’s Jubilee
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
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