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Thesis: Generative Model Assisted Sampling of Multiscale Dynamical Systems

Thesis research resulted in four publications, see Google scholar page or publications section.

Focus: Machine learning and probability theory

Minor: Mathematics

• Working on machine learning applications in anesthesia and predictive analytics to improve patient outcomes.
• Contributed (so far) to six currently pending publications and presentations. Check back here or at my Google Scholar page once they are accepted!

• Supported the biological and physical sciences division as well as the materials and processes division, primarily focusing on computational modeling and data science methods.
• Developed machine learning models to predict properties of specific materials and generate alloy compositions consistent with prescribed microscopic properties and developed code to simulate aluminum alloys undergoing welding and validated the produced data experimentally.