CS student at Xuzhou Institute of Technology (Year 3, GPA 3.83/4.0). I work on machine learning problems — mostly where math and real data meet hard constraints.
WSI cancer segmentation — built a U-Net segmentation pipeline to detect Micropapillary Adenocarcinoma from 30 whole-slide histopathological images using PyTorch and OpenCV. handled class imbalance with focal loss and patch oversampling. trained on RTX 4070, 13k+ image-mask pairs.
ML competition (Kaggle) — binary classification on tabular data. CatBoost + LightGBM + XGBoost ensemble tuned with Optuna. private AUC: 0.8938, Top 4 / 20+ teams.
Teaching assistant — C++ (x2 semesters), SQL & database management, Java web development. three courses, two years, ~15 students each.
languages: python · c++ · java · sql
ml/dl: pytorch · scikit-learn · xgboost · lightgbm · catboost · optuna
cv: opencv · u-net · patch extraction · wsi processing
data: numpy · pandas · jupyter
tools: git · linux · vs code
- year 3, graduating june 2027
- open to research collaborations in medical imaging / applied ML
- applying to summer research programs (medical imaging, deep learning for pathology)