Summary
Alexander Ruch is a Head of Community and Graph Machine Learning with nine years of experience building production-grade ML systems that blend networks, language, and time-series data to solve real-world problems. He currently leads graph ML at Lore to create the world’s largest health idea network that drives durable behavior change, and advises Sevenn on AI-driven social products that prioritize meaningful time with loved ones. Previously he built and scaled graph and multimodal ML at S&P Global, Spotify, and Graphika, hiring and mentoring teams while productizing models and MLOps for complex enterprise workflows. His Cornell PhD in computational social science informs a rare combination of rigorous experimental methods, network science, and interpretable deep learning—work published in venues like Science Advances and supported by NSF/NIH grants. He has hands-on experience deploying models over terabyte-scale, distributed datasets and designing human-in-the-loop systems for attribution, entity resolution, and community-level interventions. Based in Dallas, he bridges public-health training (MPH) with cutting-edge ML to make networks a lever for healthier communities.
9 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (PhD) Sociology and Information Science, Doctor of Philosophy (PhD) Sociology and Information Science at Cornell University
Master of Public Health Community Health and Health Behavior, Master of Public Health Community Health and Health Behavior at University at Buffalo
Master of Arts (MA) Sociology, Master of Arts (MA) Sociology at University of Iowa
Bachelor of Arts Sociology, Bachelor of Arts Sociology at SUNY Geneseo