Lei (Ray) Ge, Ph.D.
About Lei (Ray) Ge, Ph.D.
Lei (Ray) Ge, Ph.D., is a Quantitative Modeler II at Fannie Mae in the Washington D.C. Metro Area, specializing in real estate machine learning models.
Title and Current Role
Lei (Ray) Ge, Ph.D., serves as a Quantitative Modeler II at Fannie Mae in the Washington D.C. Metro Area. He has been with Fannie Mae since February 2019. In his role, Lei designs and builds real estate machine learning models, leveraging tools such as Python, JupyterLab, and SageMaker. His work combines economic theories with big data technology to enhance model development within the real estate sector.
Education and Academic Background
Lei Ge holds a Doctorate Degree in Economics (with a focus on real estate economics) from Georgetown University, where he studied from 2013 to 2018. Additionally, he earned a Master of Arts (M.A.) in Economics from Vanderbilt University, completing his studies from 2011 to 2013. Lei began his academic journey at Beijing Normal University, where he graduated with a Bachelor of Arts (B.A.) in Economics and Finance, studying from 2006 to 2011.
Previous Academic Roles
Before joining Fannie Mae, Lei Ge held several academic positions. He served as a Research Associate at Georgetown University's McDonough School of Business for five months from 2018 to 2019. From 2014 to 2018, Lei worked as an Instructor, Recitation Instructor, and Research Assistant at Georgetown University. Prior to that, he was a Research Assistant in the Economics Department at Vanderbilt University from 2011 to 2013.
Conference Presentations
Lei Ge has presented his modeling works at various prestigious conferences. His contributions include presentations at the American Real Estate Society, the American Real Estate and Urban Economics Association, and the ASSA annual conference. These presentations underscore his active engagement in the academic and professional communities of economics and real estate.