Fernando Martínez

I am a second‑year PhD student in Computer Science specializing in deep reinforcement learning and machine learning.

Lately my research centers on decision‑making under uncertainty, connecting reinforcement learning with game‑theoretic modeling and optimization to build scalable, reliable agents.

Previously, I worked in applied machine learning and data science roles, where I have applied quantitative analysis, experiment design, and develop ML models for diverse business solutions. Throughout 7 years of experience, I have had the opportunity to design and create models that are helping organizations manage risk behavior profiles, reduce tax gaps, and build advanced analytical engines for forecasting and detecting deviations from unstructured information.