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Predictive Modeling
Machine learning for classification, ranking, and decision support, with attention to evaluation and the operational consequences of model outputs.
MACHINE LEARNING · APPLIED AI · DATA ANALYTICS
Researching, teaching, and building with data.
I’m Andy Sinclair, an Assistant Professor and Chair of Business Analytics and Applied Technology at Wilmington University, a Computer Science PhD researcher at Florida Atlantic University, and the founder of RepoReport.
My work focuses on machine learning, applied AI, and analytics for operational decision-making — especially predictive modeling, ranking, workflow optimization, and decision support in the auto-repossession industry.
Assistant Professor & Chair
PhD · Expected Spring 2027
Founder, RepoReport
ABOUT
Academic research shaped by real operating experience.
My career has moved between analytics, technology, operations, higher education, and entrepreneurship. That combination shapes how I approach research: a model has to do more than perform well in a notebook — it has to help someone make a better decision in the real world.
At Wilmington University, I lead Business Analytics and Applied Technology programs while teaching across data analytics, visualization, forecasting, simulation, and optimization. My doctoral work at Florida Atlantic University centers on machine learning and applied decision systems.
2025
Fulbright Specialist
2025
Paul R. Lawrence Fellowship
2026
VISTA NextGen Superstar 40 Under 40
2026
Adjunct Professional Member, University of Delaware Data Science Institute
RESEARCH & FOCUS
Applied machine learning for consequential decisions.
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Applied AI
Practical uses of AI and generative AI in business and education, including AI literacy, responsible use, and decision-oriented workflows.
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Analytics & Visualization
Turning data into explanations and decision tools through analytics, visualization, forecasting, simulation, and optimization.
SELECTED PUBLICATIONS
Recent work.
Assessing Skip-Tracing Information in Repossession Prediction Using Ensemble Learning and SHAP Analysis
View DOI ↗Predictive Modeling for Auto Repossession Success: A Comparative Evaluation
View DOI ↗Unlocking Machine Learning Insights into a Novel Auto Repossession Dataset
View DOI ↗Applying Machine Learning to Classify Automobile Repossession Success
View DOI ↗
SPEAKING & INDUSTRY
Connecting research to the people doing the work.
I regularly work across academic and industry audiences, translating analytics and AI into practical questions about operations, workflow, decision-making, and implementation.
My conference work has included research on the auto-repossession industry, AI-assisted account review, data-driven repossession, and generative AI for interactive learning.
REPOREPORT
Building decision support for an industry I know firsthand.
I founded RepoReport in 2023 to improve repossession order intake, grading, and decision support through data-driven software. The platform translates operational information — including vehicle, address, and skip-tracing data — into tools agencies and forwarders can use to prioritize assignments and improve workflow.
RepoReport is also where my industry experience and academic research meet: operational problems inform research questions, and research helps shape more rigorous products.
BEYOND THE WORK
Curiosity should extend beyond the office.
Not everything needs a model, a dashboard, or a conference slide. I also make room for experiences that are completely different from my day-to-day work — including getting underwater and a little closer to sharks than most people would recommend.
CONNECT
Research, teaching, industry, or a useful problem?
I’m interested in collaborations involving machine learning, applied AI, analytics education, operational decision systems, and the auto-repossession industry.