Understanding & designing living(-like) matter
Complex physicochemical processes can be understood and controlled in terms of free-energy landscapes, which map metastable states and pathways onto key system descriptors. These surfaces can be explored via advanced simulations; exploiting machine learning and data mining to find optimal descriptors and boost the sampling of functional dynamics. Most importantly, in silico we can sculpt the shape of these landscapes; reshaping valleys and channels by tuning internal or external system parameters via optimization approaches and generative models. We work in reverse-engineering materials at different scales and levels of complexity—e.g., from patchy particles to molecular crystals, to proteins—and collaborate with various computational and experimental groups on diverse applications for sustainability and health.
I studied Engineering Physics at Tecnológico de Monterrey in Mexico, where I also worked for the cement and steel industry. I later completed a MSc in Computational Science and Engineering at TU München. For my thesis, I worked on adaptive quantum mechanics/molecular mechanics simulations of proton transfers and Bayesian inference of reaction coordinates in the group of Prof. Karsten Reuter. Supported by a personal fellowship, I completed my PhD cum laude in the group of Dr Bernd Ensing in HIMS Computational Chemistry. I focused on developing and applying path-based methods to understand complex chemical and conformational processes in a wide variety of biomolecules. Additionally, I worked on machine learning approaches to discover optimal descriptors for molecular transitions. Subsequently, I joined the Soft Condensed Matter group of Prof. Marjolein Dijkstra at Utrecht University, where I worked on bottom-up design of self-assembly in soft and porous materials at colloidal scales.
Since 2023, I am an assistant professor in the Computational Soft Matter Lab. My current interests include the design of complex free-energy landscapes in molecular and colloidal systems for applications in sustainability and biomedicine.
PhD in Computational Design of Soft Materials
Postdoctoral position on Artificial Intelligence for Sustainable Molecules and Materials (AI4SMM): Salt hydrates for thermal energy storage (with Prof. N. Shahidzadeh and Prof. S. Woutersen)
Postdoctoral position on Artificial Intelligence for Sustainable Molecules and Materials (AI4SMM): Plant protein mixtures for sustainable food (with Prof. P. Bolhuis, Dr. H. van Hoof, Dr. S. Jabbari-Farouji, Dr. F. Quattrocchio and Prof. P. Schall)
MSc & BSc projects
Interested in designing new molecules and materials via simulation, machine learning and data mining? Contact me.