Stochastic processes provide a rigorous framework for modelling systems that evolve over time under uncertainty, while extremal theory offers the tools for understanding the behaviour of rare, ...

Editor's note: As the following article is a chapter (Chapter 8) from David Koenig's book, Practical Control Engineering: Guide for Engineers, Managers, and Practitioners (MATLAB Examples) (McGraw ...

Simulation research derives new methods for the design, analysis, and optimization of simulation experiments. Research on stochastic models develops and analyzes models of systems with random behavior ...

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions via a process called cell fate determination. The fate of individual cells, ...

Stochastic processes are at the center of probability theory, both from a theoretical and an applied viewpoint. Stochastic processes have applications in many disciplines such as physics, computer ...

Our research focus here employs probabilistic and analytic methods to explore complex random systems. At its core, the methods developed and utilized include a wide array of tools from stochastic ...