Computer Science & Mathematics at the University of Wisconsin–Madison
I build machine learning systems and applied modeling tools with an emphasis on reproducible evaluation, clear system boundaries, and measured results.
Inference engineering extensions for MiniMind, including static KV caching, dynamic request batching, and observable FastAPI serving. Reproducible CPU microbenchmarks compare cache and batching configurations while documenting their experimental limits.
PyTorch · FastAPI · Static KV Cache · Dynamic Batching · Prometheus
A leakage-aware modeling benchmark, SHAP evidence bundle, and validated reporting API. A fixed-parameter evaluation records CatBoost OOF RMSE 4.870 against a training-fold mean baseline of 6.890 across 430 eligible companies.
CatBoost · SHAP · scikit-learn · FastAPI
2025 Zhixiang Cup · Grand Prize
The award applies to the original competition case; the repository documents the subsequent engineering release.
Machine learning systems · Applied mathematics · Interpretable modeling · Quantitative research