TAAS 2025 Speakers

The theme for TAAS 2025 is “Leveraging AI in Fundraising – Opportunities and Challenges. Speakers and topics have been selected that address this theme to create a program that focuses on both theory and practice. We look forward to the conversation!
Colton Strawser

Ryan Jackson

University of Virginia

Your AI Can’t Prospect from What it Doesn’t Know: Collection Management for Advancement

Biography
Ryan Jackson is the Associate Director of Advancement Data and Analytics at the McIntire School Foundation, supporting the McIntire School of Commerce at the University of Virginia. He served on the Policy and Practice subgroup of UVA Advancement’s AI Task Force and continues to contribute to AI strategy as a member of the University Advancement Technology Steering Committee. He holds degrees in philosophy from the College of William & Mary and in divinity from Princeton Theological Seminary.
Colton Strawser

Andrew Gutierrez

Cleveland Clinic

Creating a Comprehensive Philanthropic Revenue Projection System: A Case Study

Biography
Andrew Gutierrez is a Chicago-based philanthropy data scientist who has worked in the fundraising space since 2018. He has held roles such as Systems Analyst and Data Scientist at Cleveland Clinic’s Philanthropy Institute, and Associate Director of Development Operations at Northwestern University’s Feinberg School of Medicine. He has been the Vice President of Apra’s Illinois chapter since 2025, and he is also a member of the Association for Advancement Services Professional’s Education Committee. His main professional focus has been on leveraging data and technology to support organizations’ advancement efforts, with a particular focus on creating statistical models for identifying and segmenting prospects, quantifying prospect capacity and affinity, and forecasting gift outcomes.

Colton Strawser

Lauren Seo

Oregon State University Foundation

Recommendation Algorithm to Generate Interest-Based Leads

Biography
Lauren Seo is a Data Scientist at the Oregon State University Foundation, where she applies machine learning to personalize donor engagement and optimize fundraising strategies. With a background in data science and business intelligence, she brings a decade of experience transforming complex data into actionable insights across nonprofit and corporate sectors. Lauren holds an MS in Data Science from Northwestern University and earned a BS and BA in Mathematics and Business from Alfred University.
Colton Strawser
Colton Strawser
Colton Strawser

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.

Colton Strawser

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.