Summary
Derrick Cheung is a senior principal systems engineer with 8 years of experience applying probabilistic thinking to turn raw data into actionable insight for defense and space-domain problems. He blends hands-on algorithm development in target tracking (Kalman filtering, RTS smoothing) with statistical analysis, predictive modeling, and visualization to prototype data-exploitation tools. At Northrop Grumman he has led OPIR and Space Domain Awareness algorithm assessments, and previously built NLP pipelines, probabilistic graphical models, and large-scale data-mining solutions for operational datasets. Derrick’s background in electrical engineering (MS, Syracuse; BS, Michigan Tech) and practical experience tuning tracking and optimization algorithms give him a rare mix of signal-processing rigor and applied machine-learning craft. He often frames problems probabilistically and teaches models to automate decision-making, highlighting a knack for turning theoretical concepts into deployable systems.
8 years of coding experience
11 years of employment as a software developer
Bachelor of Science - BS, Electrical and Electronics Engineering, Bachelor of Science - BS, Electrical and Electronics Engineering at Michigan Technological University
Master of Science - MS, Electrical and Electronics Engineering, Master of Science - MS, Electrical and Electronics Engineering at Syracuse University