Current Research Projects
Using AI to Battle COVID-19 (Partner: Clinton Health Access Initiative)
In partnership with the Clinton Health Access Initiative (CHAI), the Business Analytics Initiative is developing an AI (artificial intelligence) system that will investigate, collate and curate myriad data sources (e.g. government, scientific, professional, public, advocacy, as well as social media, e.g. Twitter and Google Trends) to determine the nature of COVID-19 and, most importantly, understand the best practices for preventing its expansion and re-occurrence.
Building on IBM Watson Technology to Advance Sustainability in Coatings Industry (Partner: American Coatings Association)
As part of a project originally started under the former Center for Innovation Management Studies (CIMS), the Business Analytics Initiative is working with the American Coatings Association (ACA) to develop a system that will provide current information on health and environmental studies or reported effects that may be emerging on materials of interest in the ACA members’ supply chains so that they can proactively guide their formulation changes.
Current Research Affliates
Current Student Researchers
Aidan McCarthy is a senior majoring in statistics and business administration who is looking into patients with COVID-19 self-diagnosing on social media and how that data is predictive of trends in actual COVID-19 infections.
Nate Schaefer is a junior at NC State majoring in business administration and minoring in statistics. His research examines foreign influence campaigns and their predictive relationships between and across social media platforms.
Nikhil Ankolkar is a junior majoring in statistics with a music composition minor looking into how COVID-19 related twitter data can be used to classify specific COVID-19 positive tests by leveraging natural language processing.
Dominic Agnelli is a junior majoring in Statistics and minoring in Business Administration. The research he is doing currently, looks into using social media, specifically Twitter, to detect COVID-19 symptoms and possible COVID-19 positive cases.
Anthony Weishampel is a Ph.D. in the department of statistics who applied Functional Data Analysis methods to model social media users’ behaviors and classify the users based on their online activity. These models have been used to detect automated and state-linked accounts, as well as elicit other latent features of the users.
Pragna Bollam is a Master's student in Computer Science, who is curious about extracting insights from real-time Mobile Marketing data with application of Machine learning models and Functional Data Analysis. She is also exploring research around how Amazon reviews could be useful in analyzing purchase trends and product credibility for a period of time.
Previous Student Researchers
Sid Khullar received a master's in analytics at NC State, and spent his time with the BAI looking into developing a framework to analyze the effectiveness and impact of artificial intelligence on business problems.
Gijs Overgoor received a Ph.D. in marketing at the University of Amsterdam. As a visiting researcher at NC State, Overgoor used AI and visual analytics to study consumers’ interactions with images online.
Tom Rees, who received a master’s degree in analytics at NC State, researched how businesses could apply AI to data-driven projects. He was able to develop a framework that analyzes the effectiveness and impact of AI on business problems.
Iris Bennett is pursuing a Ph.D. in statistics and researched the applications of Sparse Markov Models to bot detection, and examined the spread of health misinformation on social media.
Trevor Ferree is a graduate of NC State with a degree in economics and a minor in statistics. He researched primarily focuses on social media analytics and forecasting virality of any topic. Ferree explored how healthcare workers utilize social media to express thoughts regarding COVID-19.
Rohan Mestri, a recent master's graduate in computer science, researched how deep learning can help us to better understand how to process and examine the informational content of images.