Summary
Danai Koutra is an Amazon Scholar and Associate Professor at the University of Michigan with a decade of experience studying large-scale graphs and the processes they encode. Her research blends node- and graph-level similarity methods with pattern mining—graph summarization, anomaly detection, and event discovery—to turn complex network data into actionable insights. She holds a PhD from Carnegie Mellon and has a track record of academic leadership as Associate Director for MIDAS, bridging data science research and institutional impact. Known for tackling both theoretical and applied problems, she collaborates across industry and academia, bringing rigorous graph algorithms to real-world systems at Amazon and beyond.
10 years of coding experience
6 years of employment as a software developer
Diploma, Electrical and Computer Engineering; Computer Science, Diploma, Electrical and Computer Engineering; Computer Science at National Technical University of Athens
PhD, Computer Science, PhD, Computer Science at Carnegie Mellon University
English, Greek, French, Spanish