Yuri Fahham Saporito, a professor and coordinator of the data science undergraduate program at Fundação Getulio Vargas’ School of Applied Mathematics (FGV EMAp), has been invited by the Bachelier Finance Society to present his paper “PDGM: a Neural Network Approach to Solve Path-Dependent Partial Differential Equations” at an online seminar on January 28.

Saporito’s paper describes the use of machine learning techniques to solve a generalized set of partial differential equations that appears in the areas of stochastic processes and quantitative finance.

The event is designed to provide a forum for academics and professionals to interact and share knowledge about quantitative finance.

To take part in the event, sign up here.