Nicolas Lanchier is Associate Professor at Arizona State University, School of Mathematical and Statistical Sciences.  His research interests include mathematical models introduced in the life and social sciences literature that describe inherently spatial phenomena of interacting populations consist of systems of ordinary differential equations.

• 1. Basics of Measure and Probability Theory.- 2. Distribution and Conditional Expectation.- 3. Limit Theorems.- 4. Stochastic Processes: General Definition.- 5. Martingales.- 6. Branching Processes.- 7. Discrete-time Markov Chains.- 8. Symmetric Simple Random Walks.- 9. Poisson Point and Poisson Processes.- 10. Continuous-time Markov Chains.- 11. Logistic Growth Process.- 12. Wright-Fisher and Moran Models.- 13. Percolation Models.- 14. Interacting Particle Systems.- 15. The Contact Process.- 16. The Voter Model.- 17. Numerical Simulations in C and Matlab.

“Stochastic Modeling by Nicolas Lanchier is an introduction to stochastic processes accessible to advanced students and interdisciplinary scientists with a background in graduate-level real analysis. The work offers a rigorous approach to stochastic models used in social, biological and physical sciences ... . Stochastic modeling provides a link between applied research in stochastic models and the literature covering their mathematical foundations.”  (Ben Dyhr, Mathematical Reviews, May, 2018)“There is a wide spectrum of topics discussed in this book. … It is also interesting to find several classical examples with all details. … The text is so carefully written and checked, that I was unable to find a single typo. The book can be strongly recommended to those students and teachers who want to be in line with modern probability theory and its diverse applications.” (Jordan M. Stoyanov, zbMATH 1360.60002, 2017)