Current Research
Current research projects involve initiatives from the Department of Energy to better secure the supply chain against attacks. The research focuses on developing robust security measures and protocols to protect critical infrastructure, leveraging agentic AI.
Research Experience:
Research Assistant, Stevens Institute of Technology (2026-Present)
PI: Dr. Gabriela Ciocarlie
- Joining a research lab focused on Agentic AI applications for cybersecurity challenges in software supply chains and critical infrastructure.
- Expected to contribute to research exploring AI-driven approaches, automated security analysis, and cybersecurity techniques to enhance critical infrastructure resilience
Graduate Research Assistant, New Jersey Institute of Technology (2024-2025)
PI: Dr. Zhihao Yao
Project: “Pypitfall: Dependency Chaos and Supply Chain Vulnerabilities in Python”
- Designed a research project to evaluate the prevalence of vulnerable dependencies in PyPI
- Independently designed data extraction and organization methods for Python library dependencies
- Developed Python scripts to automate data collection and configured specialized software across multiple machines for parallel data extraction
- Independently collected data from 600,000+ libraries
- Analyzed 375,000+ Python packages and identified potential exposure in 37.3% (140,000+ packages) and guaranteed exposure in 1.2% (4,500+ packages)
- Compiled technical reports documenting research findings and responsibly disclosed identified security vulnerabilities
- Co-authored a research paper accepted for presentation at the IEEE Big Data Cyber Hunt 2025 conference
- Presented research findings as first author at the IEEE Big Data Cyber Hunt 2025 conference
Research Intern, Hudson Institute (2024)
Advisor: Timothy Walton
Project: People’s Liberation Army Command and Control
- Researched how the People’s Liberation Army uses AI to enhance decentralized planning
- Systematically collected open-source intelligence from Mandarin-language internet sources to analyze China’s AI adoption in military planning
- Synthesized findings, analyzed collected data, and presented results to senior leadership
Project: SHIPS for America Bill
- Applied financial modeling techniques to analyze shipbuilding trends and developed tables and figures for the final research report, Shoring Up the Foundation: Affordable Approaches to Improve US and Allied Shipbuilding and Ship Repair
- Presented research analysis to policy fellows supporting congressional engagement
- Compiled evidence on U.S. shipbuilding competitiveness that informed congressional briefings and contributed to the development of the bipartisan SHIPS for America Bill
Research Publications:
- Mahon, J., Hou, C., & Yao, Z. "PyPitfall: Dependency Chaos and Supply Chain Vulnerabilities in Python." IEEE International Conference on Big Data (IEEE Big Data), 2025. First Author: Jacob Mahon. Presented at IEEE International Conference on Big Data (IEEE Big Data), Macau SAR, China, 2025.