I am a mathematician with a background in partial differential equations, numerical analysis, and control theory. My academic path began in Chile, where I earned both my engineering and master’s degrees in mathematics at Universidad Técnica Federico Santa María (USM) under the supervision of Prof. Rodrigo Lecaros and Prof. Sebastián Zamorano. I earned my Ph.D. (Dr. rer. nat.) at Friedrich-Alexander-Universität Erlangen–Nürnberg (FAU), Germany, under the supervision of Prof. Enrique Zuazua. During my Ph.D. I focused on continuous-time models, with a particular emphasis on developing efficient randomized algorithms—such as random-batch methods—for applications ranging from PDEs and optimal control to deep learning (e.g., dropout). I am currently a postdoctoral researcher at the University of California, Los Angeles (UCLA), in Prof. Yuhua Zhu’s group, researching continuous-time reinforcement learning, particularly in multi-agent systems. I am interested in bridging theoretical insights with practical implementations through numerical experiments, and I strive to connect rigorous mathematical analysis with emerging computational techniques.