Verification and validation of models course at GMU

Verification and Validation of Models (CSI 709/CSS 739)

Semesters offered: Fall 2020 (Online)

Computational models come in different forms ranging from machine learning models that predict/classify patterns to agent-based models that investigate emergent phenomena from a bottom-up perspective. Regardless of their form, all computational models should go through the Verification and Validation (V&V) process, which checks the correctness of the model design and performance. The proliferation of high-level frameworks and tools make it possible to bypass or overlook such steps.

This graduate-level course aims to teach and improve V&V practices, which is considered as an essential methodological step in model development. Some of the topics include terminology and history of V&V, statistics for V&V, verification techniques, validation techniques, validation of data-driven models, and validation in the absence of data, among many others. Students will further their knowledge with writing assignments and a term project.

Dr. Hamdi Kavak is an Assistant Professor at George Mason University. Learn more