Summary
Ariah Klages-mundt is an applied math PhD and co-founder who blends deep quantitative research with practical financial software experience to design resilient economic systems. Her work at Cornell focuses on network science, machine learning, and multi-agent models to understand cascades in financial and reinsurance networks and to architect more robust stablecoin designs. She previously built production risk analytics and classification systems in fixed-income firms, pioneering a firm-wide network model that directly motivated her doctoral research. Comfortable across Python, C++, Matlab, SQL and more, she combines theoretical algorithm design (from number theory and computational neuroscience) with hands-on implementation and a track record of shipping databases, simulators, and economic tools. An unusual strength is her ability to translate months of granular 10-K reading into scalable network models that reveal nonobvious systemic fragilities.
11 years of coding experience
5 years of employment as a software developer
Mathematics, Mathematics at University of Oxford
Mathematics, Mathematics at New York University
Management Science & Operations, Management Science & Operations at London Business School
BA Mathematics, BA Mathematics at Amherst College
PhD MSc (2018) Applied Mathematics Computer Science minor, PhD MSc (2018) Applied Mathematics Computer Science minor at Cornell University