Summary
Evan Misshula is a Criminal Justice PhD researcher and applied mathematician in New York who studies AI alignment, reinforcement learning, and behavioral stability under weak oversight, bringing 13 years of experience across academia, government, and non-profit research. He bridges criminological theory—deterrence, social bonds, desistance—with ML problems like supervision overfitting and scalable oversight to design systems that generalize beyond monitored training environments. His background spans financial mathematics, stochastic processes, category theory, and reproducible open-source computational research, paired with hands-on data integration and program evaluation work for large social-impact initiatives. Evan has taught programming and advanced statistics to practitioners (including police leadership), built high-performing predictive models and interactive dashboards, and managed data systems for a 1,300-client reentry program under a $12M contract. That blend of domain expertise and technical depth makes him adept at turning social-science insights into defensible, auditable ML experiments and policy-relevant tools.
13 years of coding experience