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Machine Learning & Investing With Professor Matthew Dixon

· Machine Learning,Investing,Deep Learning
  • Matthew Dixon is an Assistant Professor of Applied Math and affiliate in the Stuart Business school who researches applications of machine learning in finance. Matthew began his career as a quant in structured credit trading at Lehman Brothers before consulting for finance and technology firms and pursuing academic research. His prize winning and Intel funded research has led to new approaches, algorithms and software for fintech with additional funding from the National Science Foundation and Google to develop new technologies for fintech in partnership with the University of Michigan and Northwestern University. In 2020, he released the first textbook on machine learning in finance with Prof. Igor Halperin (NYU and Fidelity Investments). Matthew is also an associate editor of the AIMS Journal of Dynamics and Games and serves on the board of the (CFA) institute's New York Quantitative Society. He has held scientific appointments at Stanford University and UC Davis, and holds a PhD in Applied Math from Imperial College, London.Ma
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