Reza Mousavi

Assistant Professor
Unit: McIntire School of Commerce
Department: McIntire School of Commerce
Office location and address
125 Ruppel Dr
Charlottesville, Virginia 22904
Ph.D., Business Administration (Computer Information Systems), Arizona State University

MBA, Operations Management, University of Tehran

B.Sc., Engineering, Sharif University of Technology

I am a faculty member at McIntire School of Commerce at The University of Virginia. I am expert in artificial intelligence and business analytics. My research topics are related to the societal impacts and economics of social media, artificial intelligence and business analytics, user-generated content and healthcare information systems. I use machine learning, deep learning, natural language processing (NLP) along with econometrics to identify quasi experimental settings and study the underlying relationships among the constructs of interest. My work has appeared in Information Systems Research and Journal of Management Information Systems. My work has also been presented at international and national conferences such as CIST, WITS, WISE, ICIS, HICSS, and AMCIS. I won the best paper award (research-in-progress) at AMCIS.

I have taught advanced data science and business analytics, research methods, computer programming, and project management at the undergraduate, master, and doctorate levels. I have worked with leading consulting firms on a variety of data science projects. I was also a lead data scientist at State Farm Insurance Co. before joining academia.

Areas of Expertise

  • Artificial intelligence & business analytics
  • Natural language processing (NLP) & user-generated content
  • Societal impacts of social media
  • Economics of social media
  • Healthcare information systems

Journal Publications

Reza Mousavi, and Kexin Zhao. "Examining the Impacts of Airbnb's Review Policy Change on Listing Reviews," Journal of the Association for Information Systems (JAIS), forthcoming

Reza Mousavi, Raghu T.S., and Keith Frey. "Harnessing Artificial Intelligence to Improve the Quality of Answers in Online Question-answering Health Forums," Journal of Management Information Systems (JMIS), (37:4), 2020.

Reza Mousavi, Monica Johar, and Vijay Mookerjee. "The Voice of the Customer: Managing Customer Care in Twitter," Information Systems Research (ISR), (31:2), 2020.

Reza Mousavi, and Bin Gu. "The Impact of Twitter Adoption on Lawmakers’ Voting Orientations," Information Systems Research (ISR), (30:1), 2019.

Current Projects

COVID-19 Project: How U.S. Counties Reacted to "Opening up America Again!" Campaign, with Dr. Bin Gu


  • MSBA Program: GBAC MOD 3 and MOD 4- Data Analytics II and III ()
  • Graduate Commerce: GCOM 7560- Python Programming for Data Science
  • Undergraduate Commerce: CCOM 4559- Business Analytics with Python
COMM 4559: New Course in Commerce
Credits: 1–4
This course provides the opportunity to offer new topics in the subject of Commerce.
GBAC 7209: Data Analytics II
Credits: 2
The goal of the course is to introduce you to machine learning, some of the world's most powerful predictive models. The course covers topics such as machine learning algorithms, overfitting, supervised learning, cross-validation, regularization, recursive partitioning, and assembling. You will be exposed to Python and learn to write Python code. In teams, you will enter forecasting competitions to develop predictions using these algorithms.
GBAC 7215: Data Analytics III
Credits: 2
You will be introduced to natural language processing, deep learning and artificial intelligence including text analysis and image and voice recognition. You will work in Python to process a document's key words, sentiments, and topics. As the main building block of deep learning and artificial intelligence, you will learn to run neural networks. You will use Google's open-source TensorFlow to run neural networks for image recognition purpose.
GCOM 7560: Emerging Topics in Commerce
Credits: 2
McIntire aims to train students on the latest business practices and decision-making tools. While this statement describes the entire MS-Commerce curriculum, this 1.5 credit hour current topics course is designed to track analytical tools likely to change more frequently than our other courses. The specific topics and tools covered are subject to change annually, as marketplace demands change.