Danilo Chamorro Riascos

Background

About Danilo Chamorro Riascos

I am a graduate researcher at King Abdullah University of Science and Technology (KAUST), pursuing a Master of Science degree in Earth Sciences and Engineering. My research focuses on developing and applying machine learning techniques to improve near-surface imaging and seismic analysis. I have collaborated with my mentor and industry partners to create a novel machine learning method that accurately predicts surface wave dispersion curves from seismic recordings, boosting the reliability and output of the MASW seismic method. I have also proposed using medical imaging methods for seabed exploration at wind farms, which could lower costs and give us a clearer picture of underwater landscapes. I have gained hands-on experience with advanced imaging and sound wave mapping techniques, and presented our work at international workshops. Prior to joining KAUST, I obtained a Bachelor of Science degree in Geological Engineering from Universidad Nacional de Colombia, where I graduated with honors and participated in several geophysical projects and workshops. I have proven experience in geophysical services and data analysis, having worked as an intern at Ecopetrol and as a geophysics assistant at AGG. I have developed and implemented Python and Matlab codes for automated classification, cross-borehole tomography, and geoelectrical resistivity inversion. I have also enhanced the resolution and quality of the inverted models by using different regularization techniques. I am eager to contribute to innovative projects in a growth-oriented organization, utilizing my expertise in machine learning, data science, and geosciences. I am passionate about making AI more understandable and precise for seismic project analysis, and exploring new ways to integrate and interpret remote sensing data. I am a team player, a lifelong learner, and a problem solver, always looking for new challenges and opportunities to grow.