AI-Powered Analytics to Transform Student Success:Predict,Intervene,Improve

Thursday, May 28, 2026

2:30 PM - 3:15 PM East Coast USA Time

Location: Marquis Salon 12/13

Institution Type: 4-year institutions

Target Audience: Mid-level

Presenter(s)

Rishika Samala, Data Scientist (she/her/hers)

Advanced Data Analyst/Data Scientist
Indiana University
Westfield, Indiana, United States
RM

Ram Marupudi, Data Analyst/Data Scientist

Data Analyst/Data Scientist
Indiana University, United States
GD

Gina M. Deom

Team Lead, Institutional Report Development
Indiana University
Bloomington, Indiana, United States
SF

Stefano Fiorini, Ph.D.

Manager
Indiana University, United States
Tradara Dane'e McLaurine, Senior Executive Director of Campus Career and Advising Services (she/her/hers)

Senior Executive Director of Campus Career and Advising Services
IU Indianapolis Division of Undergraduate Education
Indianapolis, Indiana, United States

Session Abstract: AI-powered analytics are revolutionizing student success by turning data into timely, actionable support. This session introduces a multi-phase predictive process that begins before the semester and continues throughout, using pre-semester data such as academic preparation, financial aid, and registration patterns to identify top predictors of student success. During the term, biweekly updates incorporate live data from Learning Management Systems activity, course performance, and engagement signals, enabling advisors to act quickly. Beyond identifying priority students, we aggregate probability data at the program level to uncover collective risk trends, helping leaders allocate resources effectively. The session concludes with strategies for creating unbiased, explainable, and data-driven advising systems that achieve student success.

Keywords: Predictive Analysis, AI-powered insights, Student Success, Unbiased Models, Early Intervention