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Kachinga Silwimba



Emphasis in Data Science
B.S. Physics
M.S. Mathematical Sciences

Advisor: Alejandro Flores


My research interest lies in leveraging machine learning and deep learning techniques to develop efficient and accurate emulators for numerical climate models. By employing these advanced algorithms, I aim to overcome the computational challenges associated with climate modeling, significantly reducing computational costs while maintaining accuracy. My primary focus is creating novel methodologies that enhance our understanding of climate processes, predict future climate scenarios, and contribute to global efforts to mitigate climate change. I am committed to remaining at the forefront of this rapidly evolving field, continuously exploring new algorithms, techniques, and datasets to improve the efficiency and accuracy of climate model emulators, bridging the gap between traditional climate modeling and cutting-edge machine learning.