Matthew Dixon, a British applied mathematician with a focus on algorithmic finance. Moreover, 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 currently has funding by the Intel Corporation and he develops codes for high performance architectures. Furthermore, his work in deep learning with Diego Klabjan (NWU) brought wide recognition. Lastly, 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.
AI quant/researcher at Fidelity with a background in theoretical physics with an extensive experience in building cutting-edge statistical and advanced machine learning algorithms to solve practical problems in finance, especially within portfolio modeling, forecasting models, and optimal control models including reinforcement learning and inverse reinforcement learning.
2022 Quants of the Year : Dr. Igor Halperin & Dr. Matthew Dixon