ML Engineer · Computer Vision · Data Science NC State University — M.S. Computer Science (Expected 2026)
Two-phase deep learning pipeline (building localization + damage classification) on the xBD benchmark. JointDamageNet achieves F1=0.8136 with a single model, surpassing the xView2 Challenge 42-model ensemble winner (F1=0.8112) and achieving the highest localization F1 (0.8752) of all compared methods. NC State University · Advanced Topics in ML · Spring 2026
| Project | Description | Stack |
|---|---|---|
| Suspicious Activity Detection | Real-time weapon detection system, 87% precision, 0.85 mAP@0.5 | YOLOv8, OpenCV |
| LLM Data Dashboard | Natural language → sales data queries, Dockerized | Streamlit, OpenAI, Docker |
| Student Stress Prediction | Mental health prediction API with RF + K-Means | scikit-learn, Flask |
| GenoCompress-AI | 18.9× genomic compression via Conv1D autoencoder | TensorFlow, BioPython |
Languages: Python · R · Java · C · C++ · SQL
ML / CV: PyTorch · TensorFlow · Keras · scikit-learn · OpenCV · YOLOv8
Data: Pandas · NumPy · Matplotlib · Plotly · Power BI
Infra / Cloud: Docker · Flask · Streamlit · AWS · Azure · MySQL
Pre-MCS data analytics work: SQL Analytics · Instagram Analytics · Operational Metrics · IMDB Analysis
Open to ML Engineer, Applied Scientist, and Computer Vision roles. Available for OPT. Based in Raleigh, NC.


