Featured Projects
Autonomous AI Research Pipeline for Wheat Stress Tolerance
AI Scientist Framework + Bioinformatics Integration
Cutting-edge research project that applies my AI expertise from Johns Hopkins APL to biological discovery. This fully autonomous system generates hypotheses about genetic modifications for wheat stress tolerance, conducts literature reviews, designs experiments, and executes simulations using AlphaFold 3 protein folding and APSIM crop modeling - representing the intersection of AI research and practical agricultural applications.
CyberEnv - Ultra-Realistic Cybersecurity Training
AI Penetration Testing Agent Training Environment
Advanced simulation environment that leverages my cybersecurity experience from NSA to create ultra-realistic training scenarios for AI penetration testing agents. Built with QEMU/KVM virtualization, dynamic vulnerability injection, and multi-modal observations using reinforcement learning architectures, bridging my practical cybersecurity knowledge with cutting-edge AI research.
Forensic Analysis Graph Visualization
AI-Powered Evidence Relationship Discovery
Advanced forensic analysis tool developed during my research at University of Baltimore, connecting to my published IEEE COMPSAC 2025 paper. This system extracts and visualizes complex relationships from large datasets, featuring automated evidence linking, data correlation, and interactive graph visualization for digital investigations using Large Language Models.
AutoResumeAgent - Intelligent Job Application Assistant
AI-Powered Job Application Automation System
Full-stack application combining my software development skills with AI automation expertise. This browser extension uses server-side AI processing for intelligent job application automation, featuring CrewAI orchestration, anti-bot protection, and personalized response generation with ATS optimization - demonstrating practical application of AI in workflow automation.
Spark MApp - Parking Navigation & Management
Flutter + Node.js Parking Solution
Comprehensive Flutter application for parking lot discovery, navigation, and management with Mapbox integration, Stripe payments, real-time GPS navigation, and cross-platform support with extensive bug fixes and optimizations.
Tree Finder - XML Graph Converter
High-Performance Data Processing Engine
Optimized C++ program for processing large XML files to extract strings and associations, building graphs with efficient memory usage and parallel processing capabilities using TinyXML-2 and OpenMP.
Research & Publications
About
I'm a cybersecurity researcher and AI developer focused on building autonomous intelligent systems that solve complex real-world problems. Currently pursuing an M.S. in Data Science at Johns Hopkins University while working as a cybersecurity analyst at the National Security Agency and conducting AI research at Johns Hopkins Applied Physics Laboratory.
My academic background includes a B.S. in Cyber Forensics from the University of Baltimore (Summa Cum Laude, 2025), where I developed expertise in digital investigations and evidence analysis. This foundation, combined with my current graduate studies, allows me to bridge the gap between traditional cybersecurity and cutting-edge AI research.
My professional experience spans from executing realistic cyber-attack simulations and threat analysis at NSA to developing scalable ML workflows for real-time cybersecurity monitoring at APL. I've also led cross-team AI workshops at Qubit Labs and published research on using Large Language Models for judicial digital forensic evidence reconstruction.
Current Focus: Developing AI agents that can autonomously conduct scientific research, discover vulnerabilities, and automate complex workflows while maintaining human oversight and safety.
Professional Experience
- Execute realistic cyber-attack simulations and design mitigation strategies for complex threat scenarios
- Perform comprehensive network assessments to identify vulnerabilities and recommend defensive measures
- Analyze security events to drive proactive threat hunting and incident response operations
- Ensure alignment with organizational security policies and regulatory compliance requirements
- Develop scalable ML workflows for real-time cybersecurity monitoring and anomaly detection systems
- Design application frameworks for deep learning models, accelerating analysis processes by 50%
- Create modular integration tooling and reference architectures for cybersecurity applications
- Collaborate on research initiatives that simplify and enhance security research methodologies
- Spearhead AI integration across consumer applications, embedding automation to enhance user engagement
- Manage internal ML toolkit development with standardized pipelines for rapid prototype-to-production
- Lead cross-team AI workshops to educate developers and streamline deployment processes
- Coordinate between technical teams to ensure successful delivery of AI-powered features
- Lead research applying AI to extract and visualize complex relationships from large forensic datasets
- Evaluate machine learning models for automated evidence linking and data correlation in legal contexts
- Optimize algorithm performance for accuracy, throughput, and scalability in forensic analysis
- Customize large language models to support advanced data-driven investigations
Education & Credentials
Focus on machine learning, statistical modeling, and AI research methodologies
Specialized in digital investigations, evidence analysis, and cybersecurity fundamentals