Angie Moon is a Bayes-driven PhD researcher and entrepreneur based in Cambridge, MA, who builds scalable AI decision partners that awaken entrepreneurial insight through simulation, optimization, and probabilistic modeling. With eight years of experience spanning co-founding NextOpt and research roles at MIT, Columbia, and Seoul National University, she applies theoretical synthesis to practical problems in transportation, supply chains, and military logistics. Her work blends advanced Bayesian methods (Stan, simulation-based calibration) with system dynamics and Laplace/adjoint techniques to make complex models robust and actionable. She has a track record of turning hierarchical and seasonal models into measurable improvements—such as a 30% boost in engine-failure prediction accuracy and sub-5% demand-forecasting error—while organizing community-facing tutorials for model checking. At heart she pairs deep math (differential geometry foundations for approximation validity) with entrepreneurship, aiming to package rigorous inference into decision tools founders and analysts can use.
9 years of coding experience
6 years of employment as a software developer
서울대학교 (Seoul National University)
Doctor of Philosophy - PhD, Transportation, Doctor of Philosophy - PhD, Transportation at Massachusetts Institute of Technology
Pre-doc, System Dynamics, Pre-doc, System Dynamics at MIT Sloan School of Management
Master's degree, Industrial Engineering, Master's degree, Industrial Engineering at Columbia University in the City of New York
Contributions:31 commits, 54 pushes, 1 branch in 1 month
workflowdataframesdata-sciencebayesianiteration
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