Sriniketh is a doctoral candidate in marketing at the University of Wisconsin-Madison. He completed his Master’s in Informatics at NYU and his Bachelor’s in Computer Science at NITK, Surathkal. Prior to joining the program, he worked as a Data Science Fellow at BuzzFeed, a Data Scientist at American Express and as a Manager of the Machine Learning Team at American Express in New York. His research focuses on developing generalizable Causal Inference frameworks using Machine Learning and its implications for Ad Measurement, Ad Targeting and Consumer Privacy. He is also interested in emerging online marketplaces and video game platforms.
Selected Submitted Journal Articles
Li, Y. & Vijayaraghavan, S. & Mallucci, P. & Hoban, P. (2020). Selling Exclusive Goods: The Need for Resale Markets Journal of Marketing Research
Muniyappa, T. & Vijayaraghavan, S. & Das, A. & Thilagam, P. (2015). Dynamics of multi-campaign propagation in online social networks International Conference on Data Science and Advanced Analytics
Marketing Science Conference (2022) A Doubly Robust Estimator for the Front-Door Criterion
Theory + Practice in Marketing (2022) Celebrity Endorsement Effects: Evidence from Esports
Haring Symposium (2022) Celebrity Endorsement Effects: Evidence from Esports
Marketing Science Conference (2021) Celebrity Endorsement Effects: Evidence from Esports
Marketing In A Digital Age (MKT 355), Spring 2021.
A foundational understanding of digital marketing channels and how successful marketing campaigns use the numerous online and mobile platforms. Fundamentals of digital marketing including internet marketing strategies, user-generated content, search engine optimization, website design and management, inbound marketing, email marketing, social media campaigns, mobile apps, content strategy and paid search advertising.