Thesis Title: Enabling Accurate and High-Throughput Kinetics Predictions via Message Passing Neural Networks Sample projects:• Developed and tuned a graph convolutional network (GCN) to accurately predict reaction barrier heights• Created new kinetics dataset with high-quality CCSD(T)-F12 calculations• Created new Python software to automate kinetic model construction and refinement• Substantially improved estimates for thermodynamic and kinetic parameters within… Show more Thesis Title: Enabling Accurate and High-Throughput Kinetics Predictions via Message Passing Neural Networks Sample projects:• Developed and tuned a graph convolutional network (GCN) to accurately predict reaction barrier heights• Created new kinetics dataset with high-quality CCSD(T)-F12 calculations• Created new Python software to automate kinetic model construction and refinement• Substantially improved estimates for thermodynamic and kinetic parameters within RMG-database• Created kinetic model to understand pyrolysis of a surrogate mixture of heavy oil Show less

• Trained logistic regression and LightGBM models to predict income• Used SHAP values to analyze how unfairness mitigation impacts model structure • Contributed to the open source fairlearn repo

• Led team in training a linear latent variable regression model to predict species concentration from spectra • Analyzed the model’s physical interpretability and created internal tooling for reproducibility

• Collaborated with cross-disciplinary team to bring intelligence to the Fluid/Loop table component• Trained random forest to achieve 83% f1 score; outperformed XGBoost, MLP, and a heuristic baseline

• Developed a novel device to dramatically improve the image quality of cells on automated microscope system• Trained a state of the art computer vision algorithm (MRCNN) to automatically identify cells and extract numerous quantitative insights from microscope images

Used cell membrane-coated nanoparticles to create a biomimetic drug delivery platform.