Fernando Martínez-López

I'm a PhD student in Computer Science at Fordham University, supervised by Juntao Chen.

I study reinforcement learning, representation learning, and world models. I connect representation learning and control with game theory and optimization. My current focus is decentralized multi-agent learning using world models.

My first-author work includes SCORER (ICLR 2026) and CORAL (IJCAI 2026).

I'm looking for a research internship in reinforcement learning for summer 2027.

Fernando Martínez-López

Selected research

Full publication list

Experience

May – Jul 2025

Fordham–IBM Research Intern

Fordham University

Collaborative research on representation learning and reinforcement learning using Stackelberg games and bilevel optimization. First-author work published at ICLR 2026.

Jul 2023 – Aug 2024

Quantitative Modeling, Assistant Vice President

MUFG Americas · CCAR Capital Planning

Developed quantitative models and automated an interconnected capital planning model suite, with validation, performance monitoring, and stress testing.

Sep 2021 – Jul 2023

Data Scientist

Smart Energy

Built end-to-end machine learning models and ran A/B experiments to support marketing campaigns for more than 10,000 warm leads.

Full CV and experience

Outside research

I studied jazz guitar at the Santo Domingo Conservatory for three years. I'm still a jazz nerd, and these days I'm also learning chess.

You can reach me at f.martinezlpz@gmail.com.