MS CS @ UT Arlington (GPA 3.92/4.0) • Python • SQL • APIs • Power BI • ML • Cloud
I build end-to-end analytics, dashboards, and scalable backend systems with measurable impact.
- Built standardized Python data-cleaning pipelines across multiple datasets, reducing inconsistencies and accelerating ML cycles.
- Engineered ASP.NET Core + REST APIs + SQL services, improving throughput & performance for high-volume transactions.
- Created Power BI dashboards to track KPIs and enable data-driven decisions.
- Worked on annotation/validation (CVAT) to support deep learning research for image segmentation.
Languages: Python • Java • C# • JavaScript
Backend & APIs: ASP.NET Core • Flask • Django • REST • JSON • JWT • OAuth 2.0
AI / Data: ML • TensorFlow • PyTorch • Pandas • NumPy • ETL • Model Evaluation • Power BI
Cloud/DevOps: AWS • Docker • Kubernetes • CI/CD • Git/GitHub • Microservices
Databases: MySQL • PostgreSQL • MongoDB • Snowflake • BigQuery
- AI Analytics Copilot — NL → SQL analytics workflow on PostgreSQL, insights + charts.
- Personal Finance Tracker — secure expense tracking, budgeting, REST APIs, auth (JWT/OAuth), Docker + AWS.
- Thing Translator — MobileNetV2 transfer learning, TensorFlow Lite on-device inference, Android object-to-speech.
- House Sales Price Analysis — EDA + regression modeling with scaling + polynomial features; visual insights.
- Movie Genre Prediction — NLP pipeline with TF-IDF + supervised models for genre classification; Kaggle submission.
- Diabetes Prediction — classification pipeline with preprocessing + evaluation metrics; Kaggle challenge submission.
- Create Generative AI Applications on Google Cloud (Google)
- Machine Learning Operations (MLOps) for Generative AI (Google)
- Python for Data Science (IBM)
