Software Development | Computational Modeling | Machine Learning
Ph.D. candidate in Chemical Engineering at the University of Minnesota. My background involves a strong foundation in applied mathematics, computer science, and industrial process engineering. My research focuses on computational models. I am passionate about turning complex data into practical, high-impact solutions
Contact: rbarry -- at -- umn.edu
Thesis: Computational Models for Thin Liquid Films
Developed strong quantitative and analytical skills through rigorous coursework in Probability Theory and PDEs.
Built sentiment analysis systems using BERT models on large-scale Amazon review datasets.
Minors in Mathematics and History
Barry, R. & Kumar, S. (2026)
Non-uniformities in miscible surfactant-laden two-layer thin liquid films. Journal of Fluid Mechanics.
Barry, R. & Kumar, S.
Early-Stage Drying of Multicomponent Thin Liquid Films (Under Review)
Barry, R. & Kumar, S.
Early-Stage Crystal Growth Model for Drying Thin Liquid Films (Under Review)
Programming: Python, C/C++, Julia, SQL, Java
Tools: PyTorch, Docker, Git, Apptainer, Vim, VS Code
Interests: Spectral methods, diffusion models, deep learning, optimization, data engineering, reinforcement learning, physics-informed neural networks
Languages: English, French
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