I am a Chemical Engineer working on on hybrid modeling to tackle challenges in process and product development. I got my undergraduate degree in Chemical Engineering from the University of Costa Rica, with an undergraduate thesis on reactor engineering for advanced oxidation processes for wastewater treatment. I worked as a lecturer for the School of Chemical Engineering at the University of Costa Rsica, teaching statistics, thermodynamics, and reaction kinetics. I received the degree of Ph.D. in Chemical Engineering from Louisiana State University. My dissertation work studied hybrid modeling for the understanding and optimization of electrochemical systems.

I am also the co-author of AI in Chemical Engineering: Unlocking the Power Within Data.

Areas of interest

1. Multiscale modeling
2. Hybrid Modeling & Scientific AI
3. Machine Learning-based surrogate modeling
4. Transfer Learning for data-driven modeling with scarce availability of data
5. Systems design and optimization

Research

The integration of Artificial Intelligence (AI) into Chemical Engineering presents an opportunity to enhance process efficiency, accelerate materials discovery, and optimize industrial operations. My research focuses on leveraging AI-driven approaches, including machine learning, hybrid modeling, and optimization, to tackle complex challenges in chemical processes. By combining fundamental chemical engineering principles with state-of-the-art computational techniques, I aim to develop innovative solutions that advance both theoretical understanding and practical applications in the field.