NonLinearities of a Ph.D.

Industrial Problems Seminar

Cristian Chica
Dapper Global

Abstract:

This talk traces a path from a mathematics PhD into industry, organized around four chapters: the PhD, Finance, a startup, and AI. The PhD chapter covers two papers and two open problems. The talk then follows that research into practice: what it takes to move from a math PhD into a quantitative strategist role at Morgan Stanley, building data infrastructure and research at the Latin American regulatory-intelligence startup Dapper, and where large language models have, and have not, changed the day-to-day work of engineering management and research. It closes with two open problems from the PhD work: extending the exclusivity analysis beyond two platforms, and bounding the probability that the Q-learning absorption conditions are ever actually reached.