Sina Davanian is a compiler verification and security fuzzing engineer at NVIDIA with a PhD in Computer Science and eight years of experience in systems and network security research. He has published and presented at top venues including Usenix Security and Black Hat, and his work has amassed over 200 citations, reflecting measurable academic impact. His hands-on expertise spans LLVM/Clang, QEMU, PIN, Capstone, Ghidra and Android static analysis tools like AndroGuard, applied to both binary and static analysis pipelines. Past roles include malware intelligence and SSL/TLS app analysis, and he has practical experience moving research into products (e.g., commercialization work at Bitdefender). Based in Los Angeles, he blends deep reverse-engineering skills with compiler-focused fuzzing research, often bridging academic rigor with production-quality tooling.
8 years of coding experience
7 years of employment as a software developer
Master of Science (M.S.), Computer Science, 110/110 (graduated with honors), Master of Science (M.S.), Computer Science, 110/110 (graduated with honors) at Università degli Studi di Trento
Future Networking Solutions, Future Networking Solutions at KTH Royal Institute of Technology
Master of Science (M.S.), Computer Science, 8.5/10 (graduated with honors), Master of Science (M.S.), Computer Science, 8.5/10 (graduated with honors) at University of Twente
Bachelor's degree, Computer Software Engineering, Bachelor's degree, Computer Software Engineering at Shiraz University
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Riverside
Optimized DECAF with elastic whole system dynamic taint analysis
Contributions:44 commits, 2 PRs, 35 pushes in 6 months
elasticsecuritytaint-analysisoptimizeddecaf
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