Specialist ITL CSD at National Institute of Standards and Technology
Vienna, Virginia, United States
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Summary
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Senior
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Top School
Dmitry Cousin is an experienced research-oriented software engineer and specialist at NIST with 8+ years in applied AI, security automation, and statistical anomaly detection, and two decades overall in software architecture and data-driven modeling. He blends deep academic training in neural network theory with hands-on implementation across CNTK, TensorFlow, PyTorch, Python/R and a wide systems stack (Rust, Go, C#, C++, .NET, SQL and graph DBs), enabling production-ready R&D from prototypes to secure cloud and IoT deployments. At NIST he focuses on adversarial AI, entropy-based data protection, and proactive policy analysis—work that sits at the intersection of machine learning, security, and standards development. Historically he has built asset-allocation and neural modeling frameworks, and carries an uncommon mix of fuzzy-logic linguistic AI experience alongside modern deep learning toolchains. Based in Vienna, VA, he is a Microsoft-certified developer who pairs rigorous mathematical modeling with practical engineering to drive measurable security and analytics outcomes.
8 years of coding experience
7 years of employment as a software developer
Neural Networks and Speech Recognition, Neural Networks and Speech Recognition at Institute of Artificial Intelligence Problems (IPII or IPAI) formerly of Donetsk, currently relocated to Kiev
SSH#17 Donetsk
Specialist, Applied Mathematics, Specialist, Applied Mathematics at Donetsk National University
Ph.D. candidate, Mathematical Theory of Neural Network Models, Ph.D. candidate, Mathematical Theory of Neural Network Models at Glushkov Institute of Cybernetics
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