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Justin Sirignano is a professor in the Mathematical Institute at the University of Oxford, specializing in mathematical and computational finance. His research group focuses on developing mathematical deep learning models for financial data and optimizing scientific machine learning methods. Sirignano has previously held positions at the University of Illinois at Urbana-Champaign and has earned his PhD from Stanford University, along with a Bachelor's degree from Princeton University. He has received funding from the UK's Engineering and Physical Sciences Research Council and the US Department of Energy for his research, particularly in mathematical finance, including deep learning models for financial datasets and high-frequency trading data. His recent work includes the development of mathematical models to analyze complex financial systems and the application of machine learning techniques to solve partial and stochastic differential equations. Justin has authored several publications and has been recognized for his teaching excellence in subjects such as Deep Learning and Machine Learning. He currently serves as the course director for the MSc program in Mathematical & Computational Finance at Oxford, which has been ranked as the number one program in the UK for mathematical finance. He is actively involved in various research collaborations and has secured substantial grants to support his work.
University of Illinois at Urbana-Champaign • Champaign, IL
Taught courses and conducted research in mathematics, with a focus on machine learning and mathematical finance.
Stanford University • Stanford, CA
Conducted research for my PhD dissertation in mathematics.
Imperial College London • London, UK
Worked on research projects in mathematics funded by various institutions.
Department of Politics and International Relations - Higher Level English requirement.