Summary
John Dunlap is a Machine Learning Engineer and seasoned security researcher with nine years of experience uncovering subtle vulnerabilities across embedded, Windows, and cloud systems. He has driven vulnerability research and exploit development at companies ranging from Trail of Bits to Trellix and Interrupt Labs, with hands-on reverse engineering of Qualcomm AArch32 targets, SOHO routers, and complex Windows patch diffing. Comfortable moving between low-level binary analysis (IDA Pro, Binary Ninja, FRIDA) and higher-level ML and SAT-solver experimentation, he blends offensive security craft with performance-focused tooling and virtualization improvements. Based in New York, he has built Red Team infrastructure, advised on technical strategy, and delivered audits for large architectures while maintaining an unusual background in music composition that informs his methodical, pattern-oriented approach to research.
9 years of coding experience
12 years of employment as a software developer
Bacholers Music, Bacholers Music at Universifty of South Florida
Master's degree Music Theory and Composition, Master's degree Music Theory and Composition at Brooklyn College