معرفی
Justin Sirignano is a Professor of Mathematics at the University of Oxford, affiliated with the Mathematical Institute. His research bridges Applied Mathematics, Machine Learning, and Financial Mathematics, developing novel mathematical frameworks and computational methods.
Education:
- B.A. in Mathematics, Princeton University
- PhD in Mathematics, Stanford University
- Chapman Fellow, Imperial College London
His research focuses on theoretical and applied aspects of machine learning, particularly in mean-field analysis of neural networks, deep learning for PDEs/SDEs, and scientific machine learning. He has pioneered methods for solving complex financial and scientific problems using data-driven approaches.
His recent publications emphasize recurrent neural networks, reinforcement learning, and PDE closure models with applications in turbulence simulation and hypersonic flows. These works span numerical methods, optimization, and stochastic processes.
Scientific Awards:
- 2014 SIAM Financial Mathematics and Engineering Conference Paper Prize
Grants & Collaborations: He has secured over $16.5 million in funding from agencies like ONR, NSF-EPSRC, and DoE. His PhD students hold positions at J.P. Morgan, Bank of America, and other institutions.
Labs & Teams: He leads research groups in Machine Learning and Mathematical Finance at Oxford, collaborating with institutions like Notre Dame, Boston University, and UIUC.
