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Faculty and Staff Profile

Lily Shen

Assistant Professor of Finance

Office: 421 Sirrine Hall
Phone: (864)656-4879

 Educational Background

Ph.D. Business Administration
Pennsylvania State University 2016

BA Mathematics, Finance
University of California, Berkeley 2010

 Courses Taught

Real Estate Principles
Real Estate Finance
Contemporary Issues in Real Estate Markets (Penn State)


Dr. Shen is an assistant professor of finance and visiting scholar of the research department at the Federal Reserve Bank of Atlanta. Her research focuses on Fintech and Proptech, in which she applies Machine Learning and Artificial Intelligence to shed light on how technology innovation can help investors and policymakers better monitor financial risks. Since Dr. Shen joined Clemson in 2016, her work has been showcased at many finance and economics conferences. She is also the single-author winner of the prestigious 2019 American Real Estate Society Manuscript Prize. She is honored to represent Clemson to give research seminars at Cambridge University, the Baruch College, and the Federal Reserve Banks. Dr. Shen is also actively involved with student mentoring and promoting Clemson's ranking within the field of business education. She created and is currently leading two Creative Inquiry (CI) projects in which finance students develop a better understanding of machine learning algorithms and apply them to research projects. Due to her effort, Clemson is the first university that offers machine learning courses to business undergraduate students. Dr. Shen’s research work has also drawn attention from Clemson alumni. She connects current undergraduate students with successful Clemson alumni from SunTrust, CoStar, Amazon, and the County Bank to help expand their professional networks and gain industry exposure. Dr. Shen is passionate about fulfilling the mission of mentoring the next generation of innovative and ethical Clemson educated leaders who will excel in an evolving 21st-century business environment.

 Research Interests

Fintech, Proptech, Real Estate, Mortgages, Machine Learning


Clemson study shows fracking resulted in lower mortgage defaults
Information Value of Property Description: A Machine Learning Approach
Yelp ML Demo (TensorFlow)
My Linkedin page