Research

Our business analytics research efforts are designed to be leveraged to solve real problems facing businesses in an effort to increase revenue, efficiency and productivity.

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.

Patterns of Digitization

The Center for Innovation Management Studies, the predecessor of the Business Analytics Initiative, developed Patterns of Digitization, a tool for assessing how global corporations and their leaders are actually implementing digital transformation.

Aashish Malik

Aashish Malik is a master’s student majoring in Economics. His project is in a collaboration with Workplace Options company, aiming to develop a predictive model capable of accurately predicting the likelihood of an employee encountering an incident in the workplace. The hypothesis posits a causal relationship between employee characteristics, the nature of the company they work for, and the probability of experiencing workplace incidents. The objective is to develop a predictive model that rigorously tests this hypothesis and subsequently forecasts potential incidents in advance for companies. This endeavor aims to be beneficial not only for the company but also for the employees.

Saloni Shah

Saloni Shah, a graduate student in computer science, excels at analyzing data to draw meaningful insights. She is actively engaged in hands-on research in natural language processing, exploring how people’s emotions change during significant events through social media. Her main focus is identifying susceptible individuals—those whose emotional states are more open to external influences. In her ongoing work, she aims to navigate the intricate dynamics of emotional shifts in the digital age, offering crucial insights into how social media impacts individuals during key events.

Jacob Britt

Jacob Britt is a junior majoring in statistics with a minor in mathematics. His current research centers around employing multivariate time series analysis techniques to examine the impact of foreign influence campaigns via social media. By analyzing the flow of information transfer through various platforms he is seeking to identify patterns and mechanisms that contribute to the dissemination of misinformation. This research aims to inform strategies for combating misinformation, potentially influencing policy-making and fostering more resilient digital environments.

Xiaoxia Champon

Xiaoxia Champon is a 4th year PhD student in Statistics and her thesis is on Categorical Functional Data Analysis with Application to Social Media. This work is motivated by a marketing study which aims to provide insights into customer relationship management on Social Media.

Landon Smith

Landon Smith is a sophomore majoring in economics with a minor in statistics. His current research involves analyzing price data among competitors of a large corporation and building a database to generate price intelligence, which will encourage more informed decisions on sales.

Ana Maria Keating

Ana Maria Keating is a junior at NC State studying marketing and minoring in statistics. Her research focuses on tracking information networks through social media.

Nate Schaefer

Nate Schaefer graduated with a major in business administration and minor in statistics. His research examined foreign influence campaigns and their predictive relationships between and across social media platforms.

David Roycroft

David Roycroft graduated with a major in Statistics and minors in Forensic Science and Science, Technology, and Society. David researched geolocation data and location prediction through time series analysis and predictive modeling.

Nikhil Ankolkar

Nikhil Ankolkar graduated with a major in statistics and a music composition minor. He looked into how COVID-19 related twitter data can be used to classify specific COVID-19 positive tests by leveraging natural language processing.

Dominic Agnelli

Dominic Agnelli graduated with a major in Statistics and minor in Business Administration. The research he did, looked into using social media, specifically Twitter, to detect COVID-19 symptoms and possible COVID-19 positive cases.

Iris Bennett

Iris Bennett received her 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.

Pragna Bollam

Pragna Bollam, who graduated with a Master’s degree in Computer Science, extracted insights from real-time Mobile Marketing data with application of Machine learning models and Functional Data Analysis. She also explored research around how Amazon reviews could be useful in analyzing purchase trends and product credibility for a period of time.

Trevor Ferree

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.

Sid Khullar

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.

Aidan McCarthy

Aidan McCarthy majored in statistics and business administration and looked into patients with COVID-19 self-diagnosing on social media and how that data is predictive of trends in actual COVID-19 infections.

Rohan Mestri

Rohan Mestri, a 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.

Gijs Overgoor

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

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.

Anthony Weishampel

Anthony Weishampel who received a Ph.D. in Statistics applied Functional Data Analysis methods to model social media users behaviors and classify the users based on their online activity. These models have were used to detect automated and state-linked accounts, as well as to elicit other latent features of the users.

NC State AI Tool is Organization’s ’Go-to Source; for News in Covid Response

The Clinton Health Access Initiative (CHAI) has worked with partner governments around the globe to strengthen health systems and save lives. CHAI worked with the Business Analytics Initiative to develop a tool that gathers and organizes data and news articles, which the non-profit can access through a user-friendly web interface.

Patterns of Digitization – Strategic Advice for Digital Transformation

Research-Technology Management Journal (March/April 2020)

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