Danai Koutra receives Presidential Early Career Award for Scientists and Engineers
Danai Koutra, associate professor of computer science and engineering at the University of Michigan, has been honored with the Presidential Early Career Award for Scientists and Engineers (PECASE), which recognizes scientists and engineers who have demonstrated outstanding potential early in their research careers.
Established by President Clinton in 1996, PECASE is the federal government’s highest recognition for early-career scientists and engineers, honoring individuals who show remarkable potential in leadership, research, and innovation. By celebrating these achievements, the award underscores the critical role that scientific research and technological advancement play in our society and in furthering national goals. This year’s recipients include nearly 400 outstanding researchers funded by a variety of federal agencies, such as the National Science Foundation, NASA, and the Department of Defense.
Koutra has made numerous influential contributions to the field of data science. Her research focuses on developing principled, interpretable, and scalable methods for discerning and summarizing patterns in large-scale data. She specializes in leveraging the inherent interconnectedness within data, modeling these relationships as graphs that can represent anything from social to neural networks. By leveraging these intricate connections, Koutra’s work allows us to derive meaningful insights from large-scale data and better understand complex systems. Her work has a wide range of practical applications in science, industry, and government, including areas such as neuroscience, precision health, recommender systems, and deep neural networks.
Her research projects include the development of algorithms that tackle tasks involving multiple networks, such as summarizing complex patterns in brain graph data for noninvasive psychiatric diagnoses. She is also exploring graph neural networks (GNNs) in novel contexts beyond traditional assumptions, improving their performance with theoretically grounded design choices. Additionally, Koutra is advancing the identification and understanding of potential pitfalls in GNN applications and proposing improved methodologies. Her groundbreaking work has been published extensively in top-tier conferences and journals, earning her several best paper awards. Notably, her 2013 work on bipartite graph alignment was honored with the 10-Year Highest Impact Paper Award at the 2022 IEEE International Conference on Data Mining (ICDM).
Koutra’s achievements have been recognized with prestigious awards including the 2024 IBM Early Career Data Mining Research Award, NSF CAREER Award, ARO Young Investigator Award, 2023 ICDM Tao Li Award, 2020 SIGKDD Rising Star Award, and 2016 ACM SIGKDD Dissertation Award. In 2020, she was named a Morris Wellman Faculty Development Professor, reflecting her exceptional achievements in both teaching and research. Before joining CSE in 2015, Koutra earned her Ph.D. and M.S. in computer science from Carnegie Mellon University, and her undergraduate degree in electrical and computer engineering at the National Technical University of Athens.
“I am deeply honored to be included in this outstanding cohort of scientists and engineers,” Koutra said. “This award recognizes the importance and impact of the work of my entire research group, as well as the support of wonderful collaborators and mentors, which has made this research possible. It not only celebrates past achievements, but also acts as an inspiration to push the boundaries of innovation in the field of graph mining and learning, as we strive to pursue high-impact applications that benefit society.”