Summary
Josh Chang is an applied mathematician, research scientist, and entrepreneurial co-founder with 12 years of experience applying advanced quantitative methods to health, medicine, and AI. He leads Sound Prediction Inc and directs Mederrata Research, translating probabilistic modeling, Bayesian inference, and transparent analytics into actionable decisions that reduce medical adverse events and readmissions. His NIH roles and postdoctoral work blend mathematical modeling of physiology (e.g., aggregation processes, mitochondrial calcium regulation) with machine-learning methods—ranging from functional nonparametric techniques to neural-network representations of Bayesian posteriors implemented in TensorFlow Probability. Comfortable across Python, Stan, R and classical math, he pairs deep theory with production-oriented data science for government and clinical settings. Based in Silver Spring, MD, he has a PhD from UCLA and a track record of turning sophisticated inference and modeling ideas into usable tools for real-world biomedical problems.
12 years of coding experience
8 years of employment as a software developer
High School Diploma, High School Diploma at Gretchen Whitney High School
Bachelor's degree, Mathematics, Bachelor's degree, Mathematics at University of California, Los Angeles
English