M.S. candidate in Psychology: Data Science in Human Behavior at UW–Madison.
I build AI systems from start to finish: multi-agent document pipelines, fine-tuned and calibrated transformers, LLM evaluation harnesses, and behavioral prediction models.
Also:
Mailroom Reloaded ·
Mailroom-Corpus-EDA ·
RVL-CDIP-Classifier ·
AeroGlobe ·
Truth & Deception study ·
The Mandalay Bay ·
Langton’s Ant
All projects with case studies →
| Languages & data | Python · R · SQL · TypeScript · MATLAB |
| Machine learning | PyTorch · scikit-learn · Hugging Face · fine-tuning · calibration · SHAP |
| AI engineering | LangGraph · multi-agent · LLM evals · vLLM · Ollama · OpenRouter · FastAPI |
| Engineering & cloud | Docker · gRPC · Spark · pytest · Quarto · AWS · Azure · GCP |
| Education | M.S. candidate, Psychology: Data Science in Human Behavior, UW–Madison (expected December 2026). B.S. Psychology, neuroscience concentration, UW–Parkside (2025). |
| Research | Cognitive neuroscience lab at UW–Parkside: EEG, and a study of truth, deception, and cognitive workload, presented at the 2025 Midwestern Psychological Association conference. |
| Before grad school | Five years in high-volume logistics, working on quality assurance, documentation, and process improvement. It is why I care about error rates, reproducibility, and cost as much as accuracy. |




