Welcome to my technical portfolio. I'm a Computer Science student building hands-on projects across artificial intelligence, computer vision, data engineering, cloud technologies, and analytics.
My work includes YOLO object detection, OpenCV lane detection, self-driving behavior cloning, Snowflake analytics, and Databricks data engineering pipelines.
Built and deployed an event-driven AWS data pipeline for synthetic e-commerce sales data.
Pipeline: Amazon S3 → AWS Lambda/Python ETL → Amazon S3 → AWS Glue Data Catalog → Amazon Athena
Highlights:
- Automated CSV processing using an S3 event trigger
- Python ETL for duplicate removal, data standardization, missing-value handling, and revenue calculation
- Least-privilege IAM permissions
- AWS Glue schema discovery and Data Catalog integration
- Serverless SQL analytics with Amazon Athena
- End-to-end AWS deployment documented with console screenshots
Technologies: AWS S3 • Lambda • Glue • Athena • IAM • Python • SQL
📁 View AWS Serverless Data Pipeline
Computer vision project applying YOLO object detection to real-world street footage.
Highlights:
- Vehicle and traffic-object detection
- Real-world street footage
- Custom detection overlays
- OpenCV video processing
- Dataset preparation and labeling
- Model visualization and preprocessing
Technologies: Python • YOLO • OpenCV • Computer Vision
Computer vision pipeline for detecting roadway lane markings from driving video.
Pipeline:
- Grayscale conversion
- Gaussian blur
- Canny edge detection
- Region-of-interest masking
- Hough Line Transform
- Lane visualization
Technologies: Python • OpenCV • NumPy
Deep-learning project designed to predict vehicle steering angles from driving images using behavioral cloning.
Pipeline:
- Driving-image ingestion
- Steering-angle processing
- Training and validation split
- Image normalization
- Convolutional neural network
- Continuous steering-angle prediction
- Trained-model export
Technologies: Python • TensorFlow • Keras • OpenCV • NumPy • Pandas • Scikit-learn
Data project demonstrating cloud data processing, SQL analysis, and analytics workflows using Snowflake.
Focus Areas:
- SQL
- Data processing
- Data validation
- Cloud data warehousing
- Analytics workflows
Technologies: Snowflake • SQL • Python • Data Engineering
Hands-on data engineering work using Databricks and modern lakehouse concepts.
Focus Areas:
- Bronze → Silver → Gold architecture
- Delta Lake
- Auto Loader
- Structured Streaming
- SQL and PySpark transformations
- Delta Live Tables
- Data pipeline development
Technologies: Databricks • Python • SQL • PySpark • Delta Lake
Python • SQL • Pandas • NumPy
YOLO • OpenCV • TensorFlow • Keras • Deep Learning • Object Detection • Behavior Cloning • Lane Detection
Databricks • Snowflake • PySpark • Delta Lake • Auto Loader • Delta Live Tables • ETL Pipelines
AWS • Power BI
Git • GitHub • VS Code • Jupyter • Databricks Notebooks
- Databricks Data Engineer skills and certification preparation
- Data engineering and pipeline automation
- Computer vision and object detection
- Cloud technologies
- AI and machine learning
- Advanced Python and SQL
Bachelor of Science in Computer Science — In Progress
Colorado State University Global
I'm building toward opportunities in:
- Data Engineering
- Data Analytics
- Cloud Engineering
- AI / Machine Learning
- Computer Vision
- Software Development
I'm particularly interested in opportunities where I can combine Python, SQL, cloud technologies, data engineering, and AI to solve real-world problems.