Nathan Brown is a software engineer with a decade of experience specializing in language models and applied ML, currently focused on LLM evaluation and training at Microsoft’s SwiftKey. He holds both BS and MS degrees in Computer Science from Clemson, where his capstone research on efficient transformer knowledge distillation was published at EMNLP 2023. His background blends production engineering (Microsoft, Ally) with security operations and incident response at Clemson’s CSOC, giving him a practical edge in building robust, secure ML systems. As co-director of CUhackit and a research-active engineer, he bridges academia and product teams to move research into real-world deployments. A detail that often surprises collaborators: he has hands-on experience discovering and fixing privilege escalation flaws in university web services, reflecting a rare combination of model expertise and security-first engineering.
10 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Clemson University
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