03Research
Two peer-reviewed papers on transformer architectures for spatiotemporal air-pollution forecasting, from my time running the compute and modeling pipeline at Georgia Southern.
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peer-reviewed publications
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GSU Research Competition wins
PM2.5
spatiotemporal forecasting focus
Publications
How I work
I built and ran a Weights & Biases–integrated GCP environment for high-compute PyTorch Lightning transformer models, the infrastructure that made the experiments reproducible enough to publish.
The through-line to my applied work is the same instinct: rigorous evaluation, honest baselines, and models that hold up when the data shifts. It’s why I trust an RCT before I trust an offline metric.
Recognition
1st & 2nd Place, GSU Research Competition
GSU Research Scholarship