Victor A. Paludetto Magri
About Victor A. Paludetto Magri
Victor A. Paludetto Magri is a Postdoctoral Researcher at Lawrence Livermore National Laboratory, specializing in parallel sparse linear solvers and algebraic multigrid methods. He has an extensive academic background in Mechanical and Civil Engineering, with degrees from Universidade Federal de Santa Catarina and Università degli Studi di Padova.
Work at Lawrence Livermore National Laboratory
Victor A. Paludetto Magri has been employed at Lawrence Livermore National Laboratory since May 2019. In his role as a Postdoctoral Researcher, he focuses on the development of parallel sparse linear solvers, particularly emphasizing algebraic multigrid methods. His work contributes to advanced computational techniques that are essential for various scientific and engineering applications.
Education and Expertise
Victor A. Paludetto Magri holds multiple degrees in engineering. He completed his Bachelor's degree in Mechanical Engineering at Universidade Federal de Santa Catarina from 2008 to 2013. He then pursued a Master's degree in the same field at the same institution from 2013 to 2015. Following this, he earned a Doctor of Philosophy (PhD) in Civil Engineering from Università degli Studi di Padova from 2015 to 2018. His educational background equips him with a strong foundation in engineering principles and research methodologies.
Background
Victor A. Paludetto Magri began his academic journey at Universidade Federal de Santa Catarina, where he worked as a Student Intern in the Computational Fluid Dynamics and Heat Transfer Lab (SINMEC) from 2009 to 2012. He later gained experience as an intern at The University of Texas at Austin from 2012 to 2013. This diverse background in research and internships has contributed to his expertise in computational methods and engineering applications.
Research Projects and Contributions
Since joining Lawrence Livermore National Laboratory, Victor A. Paludetto Magri has been actively involved in various research projects. His specialization in parallel sparse linear solvers and algebraic multigrid methods plays a crucial role in enhancing computational efficiency and accuracy in scientific simulations. His contributions are significant in advancing the field of computational engineering.