World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
8210
World Ranking
10543
National Ranking
4419

Overview

Danai Koutra is affiliated with the University of Michigan-Ann Arbor in the United States. Their research primarily focuses on the field of Computer Science, with a specialization in Artificial Intelligence and related subfields. The breadth of their work extends into Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Management Science and Operations Research, and Information Systems.

Their main topics of study include Advanced Graph Neural Networks, Complex Network Analysis Techniques, Topic Modeling, Data Quality and Management, Natural Language Processing Techniques, Explainable Artificial Intelligence (XAI), and Recommender Systems and Techniques.

Koutra has a substantial publication record with frequent venues including:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • ACM Transactions on Knowledge Discovery from Data
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Among recent papers authored or co-authored by Koutra are:

  • Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs, 2020, arXiv (Cornell University)
  • Graph Neural Networks with Heterophily, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks, 2022, 2022 IEEE International Conference on Data Mining (ICDM)
  • Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data, 2020, Journal of the American Medical Informatics Association

Danai Koutra frequently collaborates with various researchers, including Mark Heimann, Puja Trivedi, Di Jin, Tara Safavi, and Jiong Zhu.

Their contributions to academic literature also include several book publications with Springer Science+Business Media, notably titles related to Machine Learning and Knowledge Discovery in Databases published in 2023.

Best Publications

  • Graph based anomaly detection and description: a survey

    Leman Akoglu;Hanghang Tong;Danai Koutra

  • RolX: structural role extraction & mining in large graphs

    Keith Henderson;Brian Gallagher;Tina Eliassi-Rad;Hanghang Tong

  • Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs

    Jiong Zhu;Yujun Yan;Lingxiao Zhao;Mark Heimann

  • Anomaly detection in dynamic networks: a survey

    Stephen Ranshous;Stephen Ranshous;Shitian Shen;Shitian Shen;Danai Koutra;Steve Harenberg;Steve Harenberg

  • Graph Summarization Methods and Applications: A Survey

    Yike Liu;Tara Safavi;Abhilash Dighe;Danai Koutra

  • DELTACON: A Principled Massive-Graph Similarity Function

    Unknown

  • DELTACON: A principled massive-graph similarity function

    Danai Koutra;Joshua T. Vogelstein;Christos Faloutsos

  • Graph Neural Networks with Heterophily.

    Jiong Zhu;Ryan A. Rossi;Anup B. Rao;Tung Mai

  • Graph Neural Networks with Heterophily

    Jiong Zhu;Ryan A. Rossi;Anup Rao;Tung Mai

  • Detecting insider threats in a real corporate database of computer usage activity

    Ted E. Senator;Henry G. Goldberg;Alex Memory;William T. Young

  • Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs

    Jiong Zhu;Yujun Yan;Lingxiao Zhao;Mark Heimann

  • BIG-ALIGN: Fast Bipartite Graph Alignment

    Danai Koutra;Hanghang Tong;David Lubensky

  • TimeCrunch: Interpretable Dynamic Graph Summarization

    Neil Shah;Danai Koutra;Tianmin Zou;Brian Gallagher

  • DeltaCon: Principled Massive-Graph Similarity Function with Attribution

    Danai Koutra;Neil Shah;Joshua T. Vogelstein;Brian Gallagher

  • REGAL: Representation Learning-based Graph Alignment

    Mark Heimann;Haoming Shen;Tara Safavi;Danai Koutra

  • VoG: Summarizing and understanding large graphs

    Danai Koutra;U Kang;Jilles Vreeken;Christos Faloutsos

  • Unifying guilt-by-association approaches: theorems and fast algorithms

    Danai Koutra;Tai-You Ke;U. Kang;Duen Horng Polo Chau

  • DELTACON: A Principled Massive-Graph Similarity Function

    Danai Koutra;Joshua T. Vogelstein;Christos Faloutsos

  • Com2: Fast Automatic Discovery of Temporal ( Comet ) Communities

    Miguel Araujo;Miguel Araujo;Spiros Papadimitriou;Stephan Günnemann;Christos Faloutsos

  • NetSimile: A Scalable Approach to Size-Independent Network Similarity

    Michele Berlingerio;Danai Koutra;Tina Eliassi-Rad;Christos Faloutsos

  • Glance: rapidly coding behavioral video with the crowd

    Walter S. Lasecki;Mitchell Gordon;Danai Koutra;Malte F. Jung

  • Network similarity via multiple social theories

    Michele Berlingerio;Danai Koutra;Tina Eliassi-Rad;Christos Faloutsos

  • A Graph Summarization: A Survey.

    Yike Liu;Abhilash Dighe;Tara Safavi;Danai Koutra

  • Graph Summarization: A Survey

    Yike Liu;Abhilash Dighe;Tara Safavi;Danai Koutra

Frequent Co-Authors

Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
Evangelos E. Papalexakis
Evangelos E. Papalexakis University of California, Riverside
U Kang
U Kang Seoul National University
Leman Akoglu
Leman Akoglu Carnegie Mellon University
Jilles Vreeken
Jilles Vreeken Max Planck Society
Chandra Sripada
Chandra Sripada University of Michigan–Ann Arbor
Stephan Günnemann
Stephan Günnemann Technical University of Munich
Nesreen K. Ahmed
Nesreen K. Ahmed Intel (United States)
Paul N. Bennett
Paul N. Bennett Microsoft (United States)
Joshua T. Vogelstein
Joshua T. Vogelstein Johns Hopkins University

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