Younggil Song
About Younggil Song
Younggil Song is a postdoctoral researcher currently at Lawrence Livermore National Laboratory, with previous experience at Oak Ridge National Laboratory and Northeastern University. He specializes in numerical modeling and has a strong background in physics, holding a Doctorate from Northeastern University.
Work at Lawrence Livermore National Laboratory
Younggil Song has been employed as a Postdoctoral Researcher at Lawrence Livermore National Laboratory since 2021. In this role, he focuses on advanced research in material science, specifically utilizing numerical models to analyze material microstructures. His work involves applying parallel computations on Nvidia GPUs, which enhances the efficiency and accuracy of simulations related to solidification processes.
Previous Experience at Northeastern University
Prior to his current position, Younggil Song worked at Northeastern University in various capacities. He served as a Postdoctoral Research Associate from 2017 to 2018, and as a Graduate Researcher and Ph.D. Candidate from 2012 to 2017. Additionally, he was a Teaching Assistant from 2010 to 2013. His research during this time included contributions to the MEUMAPPS code, which he helped port from Fortran to C++.
Experience at Oak Ridge National Laboratory
Younggil Song worked as a Postdoctoral Research Associate at Oak Ridge National Laboratory from 2019 to 2021. During his tenure, he focused on research related to material dynamics and contributed to the understanding of precipitate behavior in materials. His work involved investigating the dynamics of Ni-based superalloys, particularly during post-process heat treatments.
Education and Expertise
Younggil Song earned his Doctor of Physics from Northeastern University, completing his studies from 2010 to 2017. He also holds a Master's degree from the same institution, which he obtained from 2010 to 2012. His undergraduate studies were completed at Konkuk University, where he received a Bachelor of Science degree from 2002 to 2010. His educational background provides a strong foundation in physics and materials science.
Research Contributions
Throughout his career, Younggil Song has made significant contributions to the field of materials science. He implemented numerical models using CUDA language for parallel computations, which are essential for predicting the dynamics of material microstructures during solidification. Additionally, he investigated precipitate dynamics in Additively Manufactured Ni-based superalloys, enhancing the understanding of material behavior under various conditions.