TAAS 2025 Speakers

Ryan Jackson
University of Virginia
Your AI Can’t Prospect from What it Doesn’t Know: Collection Management for Advancement
Biography

Andrew Gutierrez
Cleveland Clinic
Creating a Comprehensive Philanthropic Revenue Projection System: A Case Study
Biography

Lauren Seo
Oregon State University Foundation
Recommendation Algorithm to Generate Interest-Based Leads
Biography


![greg_4 (1)[60885] Colton Strawser](https://live-texas-advancement-analytics-symposium.pantheonsite.io/wp-content/uploads/2025/07/greg_4-160885.png)
Marianne Pelletier
Staupell Analytics Group
Going Old School with AI: Self Learning Model for Fundraising
Biography
Marianne Pelletier has over 35 years of experience in fundraising, with the majority in prospect research and prospecting. She is one of the first adopters of donor modeling and data mining techniques, and is now a world-renown leader on this segment of the research profession. Pelletier’s career also includes running an annual giving program and providing software and conversion consulting through the Datatel Corporation.
Pelletier is a graduate of Rockford University and earned her MBA at Southern New Hampshire University. Her recent workbook, Building Your Analytics Shop: A Workbook for Nonprofits, is available both on Amazon.com and on this website.
Ernie Fernandez
Vermont State University
Going Old School with AI: Self Learning Model for Fundraising
Biography
Ernie Fernandez serves as Director of Institutional Advancement, reporting to AVP of Communications, Alumni and External Relations Hannah Reid, and overseeing all development and alumni engagement functions as well as the ongoing integration of VTSU’s four legacy development shops with a team of 5. Prior to joining VTSU, Ernie served in a series of development roles across Harvard University. Ernie moved to Woodstock, Vermont, with his wife Alexandra in 2020 after 15 years in Cambridge, Massachusetts.
Dr. Gregory Duke
Staupell Analytics Group
Going Old School with AI: Self Learning Model for Fundraising
Biography
For over 25 years, Gregory Duke has worked in fundraising organizations in the United States and the United Kingdom, working primarily in database management and prospect research.
Dr. Duke has presented extensively on topics including probability, use of Microsoft Excel, data analytics, and related topics at the Association of Professional Researchers for Advancement (International and chapter organizations), CASE, and the Texas Advancement Analytics Symposium (TAAS). Most recently, he spoke at CASE DRIVE 2025 on identifying the probability that a prospect will make a gift. In 2022, he presented at TAAS on the similarities between advancement and sports analytics.
Dr. Duke helps Raiser’s Edge clients to optimize their database by implementing data clean-up techniques and creating reporting structures, including dashboards and SQL queries. He also facilitates data imports into Raiser’s Edge and database administration.
Dr. Duke has worked at the University of Oxford, Niagara University, Florida International University, and the Rochester Institute of Technology. For four years, he taught a graduate course in fundraising at Niagara University. In 2004, Duke earned a D.Phil in modern history from Jesus College, University of Oxford.

Muza Carraux
Carnegie Mellon University
Leveraging Snowflake Copilot: Opportunities and Challenges Through the Lens of Data Migration
Biography
Muza Carraux is the Senior Associate Director of Advancement Analytics at Carnegie Mellon University, where she applies predictive modeling in Python and transforms complex datasets into actionable visualizations. She specializes in converting Salesforce objects and Oracle tables into curated Snowflake views, which are integrated into Tableau CRM dashboards and then surfaced back into Salesforce to provide donor acquisition, behavioral trend analysis, and college participation insights. Muza has presented at the Salesforce Education Summit and CASE Drive Conference (2022, 2025). In 2022, she co-presented a webinar with Affinaquest titled “How Carnegie Mellon University Used Predictive Analytics to Identify Potential Donors and Volunteers,” showcasing a predictive model for donor and volunteer identification.