Avary Kolasinski, Ph.D.
About Avary Kolasinski, Ph.D.
Avary Kolasinski, Ph.D., is a postdoctoral researcher at Lawrence Livermore National Laboratory, specializing in variational mesh adaptation and generation. With a strong background in computational and applied mathematics, Kolasinski's research interests include deep reinforcement learning, neural networks, and mixed-precision algorithms.
Work at Lawrence Livermore National Laboratory
Avary Kolasinski has been employed as a Postdoctoral Researcher at Lawrence Livermore National Laboratory since 2019. In this role, Kolasinski focuses on advanced computational research, engaging in projects that utilize deep reinforcement learning and neural networks. The research aims to enhance scientific computing applications, particularly through the exploration of mixed-precision algorithms and their analysis. Prior to this position, Kolasinski completed a Graduate Research Internship at the same laboratory in 2018, where they contributed to ongoing research initiatives.
Education and Expertise
Avary Kolasinski holds a Doctor of Philosophy (PhD) in Computational and Applied Mathematics from The University of Kansas, where they studied from 2013 to 2019. Kolasinski also earned a Master of Science (MS) in the same field from 2013 to 2015. Prior to this, they obtained a Bachelor of Science (BS) in Mathematics from Oregon State University Honors College from 2009 to 2013. Kolasinski specializes in variational mesh adaptation and generation, with a focus on both volume and surface meshes, and has expertise in anisotropic mesh generation and analysis.
Background
Kolasinski's academic journey began at Oregon State University, where they completed their undergraduate studies in Mathematics. They then pursued graduate studies at The University of Kansas, where they served as a Graduate Research Assistant and a Graduate Teaching Assistant from 2013 to 2019. During this time, Kolasinski contributed to various research projects and taught mathematics courses, gaining valuable experience in both research and education.
Research Interests
Avary Kolasinski's research interests encompass deep reinforcement learning and neural networks, particularly their applications in scientific computing. Kolasinski explores the use of mixed-precision algorithms and their analysis, aiming to improve computational efficiency and effectiveness in data-intensive scientific applications. Additionally, their work involves the development and analysis of compression algorithms, contributing to advancements in computational research.
Professional Experience
In addition to their current role at Lawrence Livermore National Laboratory, Kolasinski has held various positions that enhance their professional experience. They worked as a Graduate Research Assistant and a Graduate Teaching Assistant at The University of Kansas from 2013 to 2019. In 2017, Kolasinski also contributed to Chegg Inc. as a Writer for Mathematical Articles, where they applied their mathematical knowledge to create educational content.