Harry 👋

Software Engineer | OMSCS (AI Track)
Cybersecurity • Python Automation • Applied Machine Learning

Engineer with a background in security and defense systems, currently focused on applying machine learning to real-world operational problems. I’m building AI capabilities on top of practical experience in automation, data processing, and reproducible system design.

My work sits at the intersection of:

• Machine learning workflows
• Security data analysis
• Python-based automation
• Operationally grounded system design

🎯 Current Focus

• Applied machine learning fundamentals
• Building reproducible AI workflows
• Model evaluation and validation
• Data preprocessing and feature engineering
• Applying ML techniques to security and operational datasets

🚀 Selected Projects

🔐 Cybersecurity Honeypot Lab

Practical security lab environment for traffic capture and analysis.

• Infrastructure-as-code deployment
• Data collection suitable for anomaly detection workflows
• Reproducible security experimentation environment

📊 Defense Data Automation

Python tooling for extracting and transforming structured defense personnel data.

• Data normalization and preprocessing pipelines
• Automation of manual reporting workflows
• Structured datasets suitable for analytics and ML experimentation

🎓 Open-Source Teaching Materials

Course resources and structured learning content for cybersecurity education.

• Hands-on lab environments
• Python scripting exercises
• Applied systems thinking

🧠 What I'm Learning (AI)

• Supervised learning workflows
• Feature engineering techniques
• Model evaluation strategies
• Practical ML experimentation
• Integrating AI into existing engineering workflows

🛠 Technical Background

Languages: Python, Bash, SQL

Data & ML:

• Pandas
• Data preprocessing workflows
• Experimentation and evaluation pipelines

Security:

• Network labs
• Defensive tooling
• Infrastructure experimentation

Tools:
Linux • Git • Cloud environments

⚙️ Engineering Approach

• Prefer simple, maintainable solutions
• Automation where possible
• Practical experimentation over theoretical complexity
• Learning through building and iteration

📈 Current Work

• OMSCS Artificial Intelligence track
• Building AI-focused portfolio projects
• Integrating ML techniques into security workflows