I build and evaluate large-scale machine-learning systems across advertising, retail measurement, search, recommendation, and contextual graphs. My work combines causal inference, machine learning engineering, and data science to create intelligent, scalable, and measurable systems.

Alongside industry work, I serve as a conference track co-chair, program committee member, peer reviewer, author, and research mentor. I have also delivered an online invited talk on MLOps for Tennessee Tech University. I welcome conversations with researchers, practitioners, collaborators, and mentees working on applied AI and data science.