Summary
Poshen Lee is a Senior Applied Scientist with 11 years of experience applying ML/AI to cybersecurity, currently advancing Cloud SIEM capabilities at Datadog after leading generative AI and graph-based detection work at ExtraHop. She has deep expertise in recommendation systems, link prediction, time-series anomaly detection, and agentic AI that automates vulnerability-to-detection mapping and translates natural-language analyst queries into validated API searches. Poshen built production DNNs and high-performance microservices that scale across hundreds to hundreds of thousands of entities, and authored early cyberattack pattern models that process millions of detections monthly. Her background combines a Ph.D. in ECE with hands-on engineering across research labs and industry, enabling her to bridge novel research (e.g., VizioMetrics) with production-grade security products. An often-overlooked strength is her focus on operational tooling—prompt optimization ecosystems and introspective feedback loops—that measurably improve model utility and analyst productivity.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Electrical and Computer Engineering, Doctor of Philosophy (Ph.D.), Electrical and Computer Engineering at University of Washington
Bachelor's degree, Physics, Bachelor's degree, Physics at National Central University
English, Chinese