Computational Materials & Data Scientist specializing in Materials Informatics using Bayesian statistics for multiscale modeling. Expertise includes developing efficient feature engineering methods for robust materials process-structure-property relationships, and integrating physics-based constraints with data-driven AI/ML models on HPC systems. Innovative R&D professional with a track record of driving technical deliverables and leading diverse teams in fast-paced research environments. Presently a final year PhD candidate, expecting to graduate in May 2026 (Spring).
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screenPFAS
screenPFAS PublicRapid screening: degradation-relevant properties of forever chemicals
Jupyter Notebook 2
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AlloyDiscovery
AlloyDiscovery PublicUniversal electronic manifolds for extrapolative alloy discovery
Python
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LeanCNN
LeanCNN PublicLean CNNs for mapping Electron Charge Density fields to material properties (S-P linkages for Density Functional Theory data)
Jupyter Notebook
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ForestFiresModeling
ForestFiresModeling PublicThe simulation of forest fires using Partial Differential Equation (PDE) and Agent-Based Modeling (ABM) methods. The wildfire propagation dynamics and their interaction with environmental factors (β¦
Jupyter Notebook 2
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