Samaneh Torkzadeh, Ph.D. serves as Assistant Professor of Marketing at the School of Business and Public Administration at University of the District of Columbia. She specializes in researching the application of artificial intelligence and machine learning in areas such as marketing and social media analytics, and corporate strategy.
Prior to joining UDC, Dr. Torkzadeh taught at Indiana University South Bend, the University of Texas Rio Grande Valley and the University of Tehran. She gained industry experience as a key account manager at Bonny Chow Company, area sales manager at Kaf Company, and sales supervisor at Pegah Company. Dr. Torkzadeh’s research has been published in the European Journal of Marketing, Journal of Strategic Marketing, Journal of Hospitality Marketing & Management, Marketing Management Journal, and Psychology Research & Behavior Management Journal.
Dr. Torkzadeh received the Excellence in Teaching with Technology award in 2023 from Indiana University South Bend. The Excellence in Teaching with Technology Award honors one faculty member per year who shows evidence of outstanding and innovative use of technology to improve student engagement and learning in any course format (face-to-face, hybrid, online). She also garnered the prestigious Trustees’ Teaching Award from Indiana University in 2023.
M.S. Data Science, Indiana University Bloomington (2023)
Ph.D., Business Administration – Marketing, University of Texas Rio Grande Valley (2017)
M.S. International Marketing, University of Tehran (2011)
B.S. Business Management, University of Tehran (2007)
Exploring Consumer Behavior through Online Reviews and Sentiment Analysis
Investigating E-commerce Trends via Big Data Analytics and User Experience Metrics
Analyzing Online Word-of-Mouth and Unstructured Media Content (text, images, videos, and audio)
Assessing Brand Impact through Digital Influencers and Visual Content Analysis
Analyzing User-Generated Content for Marketing and Competitive Intelligence
Understanding Online Community Dynamics through Social Listening and Topic Modeling