Karina Chiñas Fuentes

Karina, originally from Mexico and with roots in the Zapotec Indigenous community, holds a BEng in Nanotechnology from ITESO. In 2023 she completed the European Master of Science in Nuclear Fusion and Engineering Physics (FUSION-EP), with study periods at Universität Stuttgart (Germany) and Universiteit Gent (Belgium). Her thesis investigated the machine-size dependence of energy confinement in tokamaks using data-driven methods.

After her master’s, she worked for a year at Toyota Motor Europe on proton-exchange membrane (PEM) fuel cells for hydrogen vehicles. Her work focused on optimising the catalyst layer via molecular-dynamics simulations and physics-informed neural networks. Karina has since returned to the nuclear-fusion field, where she remains committed to advancing low-carbon energy technologies.

Karina's PhD research focuses on data integration and sensor fusion using Bayesian and machine learning methods. Her works puts special attention on computational speed of both the techniques and their implementation, e.g. using GPU acceleration.