🎓 AI/ML-informed Theoretical Physicist | EM cavities, quantum transport & complex systems 🧑💻 Mathematica & Python scientific programming 🎹 Piano as my foundation | Cello as my voice 🧑🏫 Mentor in physics and music.
AI/ML-informed theoretical physicist working at the interface of physics, engineering, and computational science, with focus on the architecture and dynamics of quantum and electromagnetic systems. Trained across analytical modeling, numerical simulation, data-driven analysis, and experimental laboratory practice, with experience translating abstract theory into implementable models, reproducible workflows, and deployable computational tools.
Background spans quantum transport, complex systems, and applied machine learning, with a strong emphasis on rigor, structure–property relationships, and physically informed computation.
Comfortable operating across academic and industrial research environments, particularly in contexts involving ill-defined problems, high-dimensional data, and model-driven decision making.
Experience includes interdisciplinary collaboration, technical communication, mentoring, and rapid acquisition of new computational tools.
Motivated by problems where mathematical structure, physical insight, and data converge to produce scalable, product-oriented, and technologically relevant solutions, including the development of scientific SaaS platforms that operationalize physics-based models and data pipelines for real-world use.
My work sits at the intersection of quantum transport, complex networks, and non-equilibrium phenomena, with a recurring focus on symmetry, irreversibility, and data-informed modeling across physical and chemical systems. In parallel, I am increasingly interested in the development of scientific SaaS: turning rigorous models, simulations, and data pipelines into scalable, reproducible, and user-facing computational tools that bridge research and application. Alongside my scientific work, I maintain an ongoing engagement with musical study and production as a counterpoint that sharpens perception and discipline.
My current projects explore transport, structure, and emergent behavior across quantum, electromagnetic, and chemical systems, integrating analytical theory, computational modeling, and data-driven approaches, with an emphasis on transforming research-grade models into reproducible, scalable, and deployable computational tools.
I work with Mathematica, Python and a range of numerical techniques to construct models, address differential systems and study high-dimensional data. Trained in piano and cello, I regard music as a parallel discipline: an inquiry into structure, rhythm and disciplined attention. This musical practice acts as a counterpoint to my scientific work, refining both method and insight.
PUE-438D / Atlixco - Jantetelco, México.
Chapultepec Eco-Park, Morelos, México.
Using Arduino to control RGB lights when playing the piano.
Tlacotenco, Morelos, México.
Centro Morelense de Artes, Morelos, México.
Cuauhtémoc, CDMX, México.
Papillon Cuernavaca, Morelos, México.
La Marquesa, EdoMéx, México.
Rancho Revolución, Cuautla, Morelos, México.
Toluca, EdoMéx, México.
Guerrero, México.
Taxco, Guerrero, México.
Wir müssen wissen, wir werden wissen. —David Hilbert.