Data Intelligence Research Group

- a student-driven research initiative at Miami University Farmer School of Business

Use Big Data and modern AI technologies to solve challenging real-world problems.

new ico(last updated on 5/7/2021)

Student Members:

Claire pic

Claire Galberg (LinkedIn)

Senior, Major in Information Systems, Minor in Human Capital Management and Spanish
Research Interests: using data analytics methods and information systems technologies to solve challening problems, such as pandemic control.

Teradata Analytics Challenge 2020 Overall Winner
Placement: M&A consultant at West Monrone Partners

Mark pic

Runze "Mark" Cao  (Linkedin)

Senior, Major in Computer Science, Minor in Information Systems
Research interests: building data systems that address the growing data deluge includes building a resource-efficient database system
Placement: Incoming graduate student admitted to the Pre-Doctoral Masters of Science in Computer Science at the University of Chicago

Yao pic

Yao Luo  (Linkedin)

Master of Science in Business Analytics

B.A. in Information Systems Analytics (Miami)
Research interests: Machine Learning in Healthcare, Computer Vision, Deep learning and Forecasting 
Teradata Analytics Challenge 2020 Finalist

Brandon pic

Brandon Pugh  (Linkedin)

Master of Science in Business Analytics

B.A. in Economics
Research Interests: Macroeconomics and Sports Analytics

Faculty Advisors:

Research Projects

  • Effects of COVID-19 Policy and Communication on Pandemic Control in US Colleges
    • In this study, we attempt to use online social media data to better understand the student perspective of their university’s reopening and COVID-19 prevention measures and its impact on pandemic control. We collected policy information and case numbers from multiple authority resources. And, we created a web crawler to scrape Twitter data related to 250 universities including tweets, retweets, replies, and likes. Based on those tweets, we gauge student sentiment toward their university’s policy and communication. Moreover, we apply a quantitative analysis approach to explore the role of university policy, student perceptions, and their interaction on pandemic control. We believe that the expected result of our work can help universities better understand the student experiences and therefore improve their policy, response, and communication strategies to survive this turbulent period.

Big Data and AI Curriculum at FSB ISA

  • ISA 414/514: Managing Big Data
    • This course provides an introduction to the storage, retrieval and analysis of unstructured and big data. Topics include web analytics, text processing, and text analytics such as sentiment analysis in unstructured data. The course will cover and use frameworks that use distributed computing, cloud-based systems for analyzing business information data that contain both structured and unstructured data. Managing big data in organizations, and visualizing big data is introduced.
  • ISA 632: Big Data Analytics and Modern AI
    • This course will further develop students’ big data and AI skills for advanced data analytics tasks. We will introduce advanced operations and functions in in-memory cluster computing and non-relational storage solutions. Moreover, we will examine advanced analytics functions enabled by in-memory cluster computing, such as distributed machine learning, real-time analytics on streaming data, and large-scale social network analysis. Following that, we will cover data-driven modern AI technologies, such as natural language processing, speech recognition, and computer vision. Those topics will be taught in an applied way, without focusing too much on the theory.
  • Industry Partners
    • Procter & Gamble Higher Education Grant
    • Cloudera Academic Program
    • Databricks University Alliance Program
    • AWS Educate Program