Kathleen Carley is a professor in the Engineering and Public Policy Department, Computer Science Department, and Social and Decision Sciences Department at Carnegie Mellon University. She is the director of the Center for Computational Analysis of Social and Organizational Systems (CASOS), a university wide interdisciplinary center that brings together network analysis, computer science and organization scienceOpens in new window, and has an associated NSF-funded training program for Ph.D. students. Carley’s research combines cognitive science, social networks, and computer science to address complex social and organizational problems. Her specific research areas are dynamic network analysis, computational social and organization theory, adaptation and evolution, text mining, the impact of telecommunication technologies and policy on communication, information diffusion, and disease contagion and response within and among groups particularly in disaster or crisis situations.

Carley and her lab have developed infrastructure tools for analyzing large-scale dynamic networks and various multi-agent simulation systems. The infrastructure tools include ORA, a statistical toolkit for analyzing and visualizing multi-dimensional networks. ORA results are organized into reports that meet various needs such as the management report, the mental model report, and the intelligence report. Another tool is AutoMap, a text-mining system for extracting semantic networks from texts and then cross-classifying them using an organizational ontology into the underlying social, knowledge, resource, and task networks. Her simulation models meld multi-agent technology with network dynamics and empirical data. Three of the large-scale multi-agent network models she and the CASOS group have developed in the counter-terrorism area are: BioWar a city-scale dynamic-network agent-based model for understanding the spread of disease and illness due to natural epidemics, chemical spills, and weaponized biological attacks; DyNet a model of the change in covert networks, naturally and in response to attacks, under varying levels of information uncertainty; and RTE, a model for examining state failure and the escalation of conflict at the city, state, nation, and international as changes occur within and among red, blue, and green forces.

Carley is the director of the center for Computational Analysis of Social and Organizational Systems (CASOS), which has more than 25 members, both students and research staff. She is the founding co-editor with Al Wallace of the journal Computational Organization Theory and has co-edited several books in the computational organizations and dynamic network area.

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Danai Koutra is an Associate Director of the Michigan Institute for Data Science (MIDAS) and an Associate Professor in Computer Science and Engineering at the University of Michigan, where she leads the Graph Exploration and Mining at Scale (GEMS) Lab. She is also an Amazon Scholar. Her research focuses on principled, practical, and scalable methods for large-scale real networks, and her interests include graph summarization, graph representation learning, graph neural networks, knowledge graph mining, similarity and alignment, temporal graph mining, and anomaly detection. She has won an NSF CAREER award, an ARO Young Investigator award, the 2020 SIGKDD Rising Star Award, research faculty awards from Google, Amazon, Facebook and Adobe, a Precision Health Investigator award, the 2016 ACM SIGKDD Dissertation award, and an honorable mention for the SCS Doctoral Dissertation Award (CMU). She holds a patent on bipartite graph alignment, and has 8 award-winning papers in top data mining conferences. Over time, she has held a variety of service roles: She is an Associate Editor of ACM Transactions on Knowledge Discovery from Data (TKDD) and a program co-chair for ECML/PKDD 2023. She was a track co-chair for The Web Conference 2022, a co-chair of the Deep Learning Day at KDD 2022, the Secretary of the new SIAG on Data Science in 2021, and has routinely served in the organizing committees of all the major data mining conferences. She has worked at IBM, Microsoft Research, and Technicolor Research. She earned her Ph.D. and M.S. in Computer Science from CMU, and her diploma in Electrical and Computer Engineering at the National Technical University of Athens.

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