I study problems at the intersection of Machine Learning, Optimization, and Game Theory. My work facilitates the application of economic models to large-scale real-world problems by studying their computational properties, and by developing optimization algorithms to solve them. In particular, I study machine learning and optimization techniques revolving around Internet advertising markets and sequential decision-making problems. The goal of my work is developing both rigorous theoretical foundations for these problems, as well as practical algorithms that can have high impact in real-world scenarios.I'm a member of the ELLIS Society.For more information about my research see my personal page: https://andcelli.github.io/