Stochastic Differential Equations, Backward SDEs, Partial Differential Equations

Etienne Pardoux: Born in 1947, graduated from Ecole Polytechnique (1970), Thesis Univ. Paris-Sud 1975, CNRS Research Assoc. 1970-79, Maître de Conférences, then Professor Univ. d’Aix-Marseille since 1979. Member of the Institute for Advanced Study, Princeton NJ, 1986-1987. Member of the Institut Universitaire de France, 1992-2002. Pardoux has published more than 140 papers on nonlinear filtering, stochastic partial differential equations, anticipating stochastic calculus, backward stochastic differential equations, homogenization and probabilistic models in evolutionary biology, and three books.Aurel Rascanu: Born 1950, Graduated from “Alexandru Ioan Cuza” University of Iasi (UAIC-Iasi), Romania (1974), Thesis UAIC-Iasi 1983, Assistant (1978-1985), Lecturer (1985-1990), Doctor (1990-1997), Professor (since 1997) at UAIC-Iasi, Dean of Faculty of Mathematics (1990-1992) and Head of the Department of Applied Mathematics (2000-2004) at UAIC Iasi. He has written 35 scientific papers. His scientific research is in stochastic differential equations, stochastic variational inequalities, approximation and numerical simulation, stochastic optimal control, viability and invariance, and probabilistic methods in the study of partial differential equations.

• Introduction.- Background of Stochastic Analysis.- Ito’s Stochastic Calculus.- Stochastic Differential Equations.- SDE with Multivalued Drift.- Backward SDE.- Annexes.-  Bibliography.- Index. ​ ​

"This 668-page magnum opus of stochastic ODEs and PDEs belongs on the shelf of every researcher in these areas, as well as any mathematician or scientist who wants to learn more about the subject. ... my opinion is that this book accomplished a Herculean task of making an arguably technical subject that is daunting to a beginner accessible. This book wants to be read!" (Mark A. McKibben, Mathematical Reviews, April, 2016) "The present monograph gives a rather complete treatment of backward stochastic differential equations as tool for the stochastic interpretation of second order PDEs. As the reader is guided from basic knowledge on stochastic analysis through the Ito calculus and the theory of stochastic differential equations to that of the backward equations, the monograph represents in my eyes a precious textbook for Master students, PhD students, but also specialists in this domain." (Rainer Buckdahn, zbMATH 1321.60005, 2015)