Nijat Rustamov, MS, PhD candidate, University of Wyoming

Application of Kinetic gas theory in computational fluid dynamics can bridge the gap between molecular and macroscopic scale models. The physics informed neural networks can then learn the underlying statistical mechanics and mimic the results within considerably shorter time frames, and help us understand the interactions between scales.


Expectations from the Seminar:

By joining our seminars, you will have the opportunity to meet fellow Azerbaijani scholars conducting scientific research or working in the field of technology. These sessions not only give you the chance to learn about their personal career paths, but also provide insights into the depth of their research and its broad impact on our modern world. You will be introduced to the latest scientific advancements in the field and gain ideas on how you can engage in such research, collaborate, or pursue similar academic paths.