Katie Adams
About Katie Adams
Katie Adams is a Graduate Teaching Assistant at The George Washington University, specializing in data-driven fashion forecasting. She holds a Master of Science in Mathematics and a Doctor of Philosophy in Statistics, with a background in both mathematics and biology.
Work at The George Washington University
Katie Adams has been serving as a Graduate Teaching Assistant at The George Washington University since 2019. In this role, she supports faculty in delivering course content and assists students in their learning processes. Her responsibilities may include preparing instructional materials, grading assignments, and providing academic guidance to students. This position allows her to apply her academic knowledge and teaching skills in a higher education setting.
Education and Expertise
Katie Adams holds a Doctor of Philosophy (PhD) in Statistics from The George Washington University, which she completed from 2019 to 2022. Prior to this, she earned a Master of Science (MS) in Mathematics from the University of North Carolina at Charlotte between 2017 and 2019. She also obtained a Bachelor of Science (B.S.) in Mathematics and Mathematics Education, with a minor in Biology, from North Carolina State University from 2013 to 2016, and a Bachelor of Arts (B.A.) in Mathematics with a Biology minor from the University of North Carolina at Charlotte in 2016-2017.
Background
Katie Adams has a diverse background in academia, having worked at the University of North Carolina at Charlotte in various roles from 2017 to 2019. Her positions included Graduate Assistant, Receptionist, Computer Language Apprentice, and Research Assistant. These roles provided her with a solid foundation in both administrative and research functions within the Department of Mathematics and Statistics. Her work experience has contributed to her understanding of the academic environment and enhanced her skills in data analysis and research.
Research Focus
Katie Adams's research interests lie in data-driven fashion forecasting, where she combines artistic creativity with data analytics. This interdisciplinary approach allows her to explore the intersection of technology and creativity, aiming to develop innovative solutions in the fashion industry. Her research reflects a commitment to applying mathematical and statistical methods to real-world problems, particularly in the context of fashion trends and consumer behavior.