Culverhouse Analytics Summit

October 8-10, 2025

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Schedule and Session Info

The Business Analytics Summit, presented by the Institute of Data & Analytics, serves as a dynamic intersection between industry and academia.

This premier event brings together professionals from both areas to create a collaborative environment where knowledge and expertise are shared. The symposium showcases current analytic practices used in various industries and highlights the latest methodological advances developed within academic research.

See below for the schedule for the Symposium on Friday, October 10 and go here for the broader Summit agenda.

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SYMPOSIUM Schedule for Friday, OCtober 10

All activities are in the Sellers Auditorium unless otherwise noted.

7:15 – 8:00 AM | Registration and Light Breakfast

8:00 – 8:15 AM | Welcome

8:15 – 9:00 AM | Juan Gorricho

9:00 – 9:15 AM | transition

9:15 – 10:00 AM | Dr. Frances Boykin – AT&T

10:00 – 11:00 AM | Poster Session — Rast

11:00 – 11:45 AM | Brooks Bourland - TransUnion

11:45 AM – 1:00 PM | Lunch — Sellers Lobby

1:00 – 1:45 PM | Koba Khitalishvili - NBA

1:45 – 2:00 PM | transition

2:00 – 2:45 PM | Frank Phillips and Dan Scruggs – Snorkel AI

2:45 – 3:00 PM | transition

3:00 – 3:45 PM | Panel Discussion: Industry & Academic Applications of Generative AI

  • Charley Irons, Assistant Professor at Texas Christian University
  • Steven Elseroad, Senior Manager at KPMG
  • Nick Ramos, Lead Data Scientist at 84.51˚
  • Jon Fahrner, Shipt, Vice President of Sales Development, Innovation and Growth

3:45 – 4:15 PM | Awards AND Closing Remarks

Schedule subject to change

Brooks Bourland

Head of Global Digital Fraud Data Science

TransUnion

Operationalizing ML/AI in the Fraud Mitigation Space

  • Fraud prevention represents a dynamic and challenging area for data science and analytics. Building and assessing performance of machine learning solutions often is the tip of the iceberg in terms of the having an impact in preventing fraud. Deployment within the real-time architecture and decision rules constitute the bulk of the work. Given this context it is critical to understand how to evaluate the performance of individual machine learning models, and in developing comprehensive, data driven, fraud prevention engines. This discussion will seek to provide an overview of how we 1) assess value of individual solutions, 2) operationalize multiple machine learning solutions, and 3) using machine learning to create optimal decision rules.

Dr. Frances Boykin

Director of Advanced Analytics

AT&T

From Data to Impact: How Analytics Drives Innovation and Opportunity in the Modern South

  • In an era where data fuels decision-making across industries, the ability to harness analytics for meaningful impact has never been more critical—especially in the fast-evolving business landscape of the American South. This keynote will explore how business analytics is transforming organizations, communities, and individual career paths, with special focus on the unique opportunities and challenges facing University of Alabama students and faculty. The session will highlight real-world examples of how analytics is driving innovation in regional industries such as healthcare, sports, finance, and manufacturing, as well as how ethical considerations and responsible AI are shaping the future of analytics. Attendees will gain insights into the skills and mindsets needed to thrive in this data-driven world, discover actionable strategies for bridging the gap between classroom theory and business practice, and hear inspiring stories of analytics making a difference in Southern communities. Whether you are an educator preparing students for tomorrow’s careers or a student seeking to chart your own path, this keynote will equip you with the knowledge and inspiration to turn data into opportunity and impact.

Juan Gorricho

Former Executive Product Owner and Data Strategy

Toronto-Dominion Bank

Beyond the Hype: The Real Work of Scaling Data and AI Solutions

  • The data industry has a dirty secret: while organizations rush to deploy AI solutions, 70-85% of these projects fail to deliver expected outcomes. After 25 years leading data transformations at major organizations such as Disney, Visa, and TD Bank, the pattern is clear: organizations build on quicksand instead of solid foundations. This presentation cuts through the hype to reveal what separates successful enterprise implementations from expensive failures. We'll explore three critical foundations most organizations skip: - Strategic Business Alignment: Moving beyond "cool demos" to solve real business problems - Data Governance at Scale: Why pilots work with clean samples but production fails with organizational complexity - Adoption as Product Strategy: Building solutions humans actually use, not technical marvels that gather dust Whether you're preparing for industry or tired of pilots that go nowhere, you'll leave with practical frameworks and specific questions to identify—and build—the foundations needed for success at enterprise scale. Warning: Contains reality checks that conflict with current AI marketing.

Koba Khitalishvili

Senior Data Scientist and AI Engineer

NBA

Analytics, ML, AI in Sports and Entertainment: From Courtside to the Cloud

  • The sports and entertainment industry is undergoing a data-driven transformation. From optimizing multi-million-dollar media investments to charting a future data strategy, organizations are turning to analytics, machine learning and AI to make smarter, faster, and more profitable decisions. In this talk, we will explore real-world applications of data science within the NBA and beyond, demonstrating how predictive models and data driven decision making can enhance revenue streams, deepen fan engagement, and transform business strategy. We will cover the evolution of marketing media mix modeling in the era of massive broadcast and streaming rights, show how clustering and regression techniques drive smarter ticket pricing strategies, and share insights into fan behavior through large-scale propensity modeling. Finally, we will look ahead to the role of generative AI and large language models in sports - highlighting how curated data platforms and embedded AI solutions can unlock the next wave of innovation. This session will blend technical depth with business impact, giving attendees a clear view of how modern analytics and AI can power decision-making across industries where data, fans, and entertainment intersect.

Frank Phillips

Applied AI Engineer

Snorkel AI

Winning with Data-Centric AI

  • Artificial intelligence has been the hottest topic of the business world the last few years. Every week there’s a new model, new vibe-coded apps, and seemingly limitless value. But in large enterprises, AI is still in its infancy. Most projects fail, and many companies are still trying to figure out how best to use the capabilities LLMs and other Machine Learning models provide. At Snorkel, we've delivered AI solutions for our Fortune 500 customers across industries in banking, telecommunications, healthcare, technology, and more. In this session, we'll explore how we delivered real-world use cases of AI through the lens of what we believe is the most important part of AI systems: the data. You’ll take away lessons on how to get AI projects to production through building high-quality datasets, targeted evaluations, and making the most of humans in the loop.

Dan Scruggs

Applied AI Engineer

Snorkel AI

Winning with Data-Centric AI

  • Artificial intelligence has been the hottest topic of the business world the last few years. Every week there’s a new model, new vibe-coded apps, and seemingly limitless value. But in large enterprises, AI is still in its infancy. Most projects fail, and many companies are still trying to figure out how best to use the capabilities LLMs and other Machine Learning models provide. At Snorkel, we've delivered AI solutions for our Fortune 500 customers across industries in banking, telecommunications, healthcare, technology, and more. In this session, we'll explore how we delivered real-world use cases of AI through the lens of what we believe is the most important part of AI systems: the data. You’ll take away lessons on how to get AI projects to production through building high-quality datasets, targeted evaluations, and making the most of humans in the loop.