About me
I am a computational materials scientist whose research integrates theory, simulation, and data science to uncover the physical principles that govern order and dynamics in complex soft materials. I am currently a Beckman Postdoctoral Fellow at the University of Illinois Urbana-Champaign, working with Prof. Nick Jackson on machine-learning-guided modeling of liquid-crystalline and anisotropic systems.
I earned my Ph.D. in Molecular Engineering from the University of Chicago, advised by Prof. Juan de Pablo. My doctoral work explored liquid crystals under chirality, confinement, and external fields to understand how nonequilibrium conditions give rise to emergent order. My computational methods bridge experimental observations with theoretical descriptions, informed by a background in Chemical Engineering from Universidad Nacional de Colombia, where I developed a strong foundation in thermodynamics and modeling.
My research develops multiscale frameworks that connect molecular identity, interfacial structure, and macroscopic behavior across length and time scales. By combining continuum theories, coarse-grained molecular simulations, and physics-informed machine learning, I aim to create predictive and interpretable models of self-organization in chemically heterogeneous materials. These approaches enable the inverse design of responsive soft systems, with applications spanning functional films, biomimetic assemblies, and food formulations as soft matter.
For more information about my ongoing projects, see the Research section.