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, ...

This course provides doctoral students the foundations of applied probability and stochastic modeling. The first part of the course covers basic concepts in probability, such as the Borel Cantelli ...

The beauty of Statistics is that if you can take a large enough group of people, you can predict really well what the outcome will be overall Our research works across the fields of probability, ...

Let X(t) be a homogeneous and continuous stochastic process with independent increments. The subject of this paper is to characterize the stable process by two identically distributed stochastic ...

Applications range from medical imaging to autonomous vehicle technology. Learn data manipulation techniques to improve signal or image fidelity. Understand the theory of probability and stochastic ...

Students must have completed or currently enrolled in a course in the equivalency group containing MATH 310-2 or MATH 311-2. Prerequisite: Students must have completed or currently enrolled in a ...

Ruin probability quantifies the risk that an insurer or financial institution’s liabilities may exceed its assets, ultimately leading to insolvency. Recent advancements in risk management have ...