Daniel Navia

Background

About Daniel Navia

Faculty at Universidad Técnica Federico Santa María (UTFSM), with over 12 years of experience in Process Systems Engineering, with applications in mining, bioprocess automation, and advanced process control. My research focuses on real-time optimization, nonlinear model predictive control, and decision-making under structural and parametric uncertainty. I am particularly interested in physics-guided AI approaches that combine first-principles models with data-driven techniques to enhance the efficiency, robustness, and interpretability of complex industrial systems—especially under uncertain operating conditions. I serve on the academic boards of the PhD in Applied Engineering, PhD in Sustainable Engineering, and MSc in Chemical Engineering programs, and collaborate with the PhD in Artificial Intelligence. I am also a researcher at the Sustainable Energy Transition Center (SET), where I support interdisciplinary work at the intersection of energy systems, artificial intelligence, and process engineering. ORCID: