Before joining Great Bay University, Jinqiao Duan was Professor and Director of the Laboratory for Stochastic Dynamics at Illinois Institute of Technology. During 2011–13, he also served as Professor and Associate Director of the Institute for Pure and Applied Mathematics (IPAM) at the University of California, Los Angeles. An expert in stochastic dynamics, stochastic partial differential equations, and their applications in engineering and science, he has been the managing editor for the journal Stochastics and Dynamics for over a decade. He is also a co-author of a research monograph, Effective Dynamics of Stochastic Partial Differential Equations (2014), based on his teaching at various universities since 1997.
'Jinqiao Duan's book introduces the reader to the actively developing theory of stochastic dynamics through well-chosen examples that provide an overview, useful insights, and intuitive understanding of an often technically complicated topic.' P. E. Kloeden, Goethe University, Frankfurt am Main 'Randomness is an important component of modeling complex phenomena in biological, chemical, physical, and engineering systems. Based on many years teaching this material, Jinqiao Duan develops a modern approach to the fundamental theory and application of stochastic dynamical systems for applied mathematicians and quantitative engineers and scientists. The highlight is the staged development of invariant stochastic structures that underpin much of our understanding of nonlinear stochastic systems and associated properties such as escape times. The book ranges from classic Brownian motion to noise generated by α-stable Levy flights.' A. J. Roberts, University of Adelaide 'This book provides a beautiful concise introduction to the flourishing field of stochastic dynamical systems, successfully integrating the exposition of important technical concepts with illustrative and insightful examples and interesting remarks regarding the simulation of such systems. Both presentation style and content are suitable for beginning graduate students in mathematics or applied mathematics who already possess an understanding of deterministic dynamical systems, as well as ordinary and partial differential equations. The book may also be of interest to applied mathematicians, as well as physicists, computer scientists and engineers who, having a sound knowledge of deterministic dynamics, wish to acquire an understanding of basic techniques for the analysis of stochastic differential equations.' Diogo Pinheiro, Mathematical Reviews