- Machine Learning
- Cybersecurity
- Malware Analysis
- +۱۲ مورد دیگر
Mark S Stamp is a tenured Professor in the Department of Computer Science at San José State University. Previously, he held roles at the National Security Agency (NSA) and the startup MediaSnap, Inc. His academic journey began with a B.S. in Computer Science and History from Morningside College, followed by a Ph.D. in Mathematics from Texas Tech University. Current role: Professor, Computer Science, San José State University Prior roles: NSA analyst, MediaSnap entrepreneur Research Interests Professor Stamp's work focuses on Machine Learning and Deep Learning applications in Cybersecurity , particularly Malware Analysis , Adversarial AI , and Steganographic Capacity . His research spans Hidden Markov Models , Federated Learning , and Android Malware Detection . Recent Publications Trend His 2025–2024 publications emphasize malware classification using hybrid models (e.g., HMM-CNN), adversarial attack analysis in federated learning, and steganographic techniques in transformer models. Additional work explores chatbot detection, energy-efficient neural networks, and cybersecurity applications of QR/Aztec code analysis and keystroke dynamics . Advising & Collaborations While specific advisees are not listed, his research engages with collaborators in AI security , mobile threat detection , and sequence modeling . His career bridges academia, intelligence, and startup innovation.
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