Hsiuhan Lexie Yang
About Hsiuhan Lexie Yang
Hsiuhan Lexie Yang is a Research Scientist at Oak Ridge National Laboratory, where she has worked since 2018. She holds a Ph.D. in Civil Engineering from Purdue University and specializes in large-scale geospatial data analysis, machine learning, and high-performance computing.
Work at Oak Ridge National Laboratory
Hsiuhan Lexie Yang has been employed as a Research Scientist at Oak Ridge National Laboratory since 2018. In this role, she leads projects within the GeoAI Group, focusing on large-scale geospatial data analysis. Her work encompasses machine learning, deep learning, and high-performance computing, contributing to advancements in the field of geospatial research.
Education and Expertise
Hsiuhan Lexie Yang holds a Doctor of Philosophy (Ph.D.) in Civil Engineering from Purdue University, where she studied from 2008 to 2014. She also earned a Master of Science (M.Sc.) in Civil Engineering from National Taiwan University from 2005 to 2007. Additionally, she completed a Bachelor of Arts in Land Economics at National Chengchi University from 2000 to 2004. Yang further enhanced her skills by obtaining a Certificate in Statistics in Applied Statistics from Purdue University between 2012 and 2014.
Previous Positions
Prior to her current role, Hsiuhan Lexie Yang worked as a Postdoctoral Research Associate at Oak Ridge National Laboratory from 2016 to 2017. She also served as a Postdoctoral Researcher at Purdue University from 2014 to 2015. Earlier in her career, she was a Teaching Assistant at National Taiwan University from 2007 to 2008, and a Graduate Research Assistant at Purdue University from 2010 to 2014. Additionally, she worked as a Graduate Teaching Assistant at Purdue University in 2011.
Research Focus
At Oak Ridge National Laboratory, Hsiuhan Lexie Yang leads research initiatives that involve the analysis of large-scale geospatial data. Her expertise in machine learning and deep learning allows her to tackle complex problems in geospatial research. Yang's work in high-performance computing further enhances the efficiency and effectiveness of her projects, contributing to the advancement of GeoAI technologies.