Dr. Danai Koutra

Associate Professor

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Biography

Danai Koutra is an Associate Professor in the Department of Computer Science Engineering at the University of Michigan, Ann Arbor, where she leads the Graph Exploration and Mining Scale (GEMS) Lab and is an Amazon Scholar. Her research centers on developing principled, practical, and scalable methods for large-scale real networks, exploring areas such as graph learning, graph neural networks, summarization, and mining knowledge graphs. Koutra holds a Ph.D. and M.S. in Computer Science from Carnegie Mellon University and a diploma in Electrical and Computer Engineering from the National Technical University of Athens. She has received numerous accolades for her work, including the Presidential Early Career Award for Scientists and Engineers (PECASE), the NSF CAREER Award, and the ACM SIGKDD Dissertation Award. Koutra’s dedication to advancing data mining techniques has resulted in her serving as a program co-chair for prestigious conferences, including ACM KDD and ECML/PKDD. Additionally, she has contributed to significant advancements in data mining communities and has held research positions at IBM and Microsoft Research.

Research Interests

Artificial Intelligence Graph Mining Graph Machine Learning Data Mining Graph Neural Networks Network Representation Learning Network Neuroscience Summarization Network Similarity Network Alignment Mining Time-Evolving Streaming Data Graph Anomaly Event Detection

Experience

Associate Professor

2019-01-01 — Present

University of Michigan • Ann Arbor, MI

Conducts research and teaches courses in computer science and engineering with a focus on data mining and graph learning.

Awards

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Presidential Early Career Award for Scientists and Engineers (PECASE)

2025-01-01
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IBM Early Career Data Mining Research Award

2024-01-01
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IEEE ICDM Test-of-Time Award

2022-01-01
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ACM SIGKDD Rising Star Award

2020-01-01
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NSF CAREER Award

2019-01-01
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ACM SIGKDD Dissertation Award

2016-01-01

Courses

EECS 476 - Data Mining EECS 576 - Advanced Data Mining EECS 598 - Advanced Data Mining / Mining Large-Scale Graph Data EECS 484 - Database Management Systems

Requirements for University of Michigan

Master Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Total
Required:84
GRE General
Verbal
Required:155
Verbal Percentile
Required:50
Quantitative
Required:168
Quantitative Percentile
Required:50
Analytical Writing
Required:3.6
Writing Percentile
Required:50
Prerequisites
Bachelor degree in engineering, physics, or mathematics Calculus Physics
Application Checklist
  • Rackham Graduate School Application
  • Official Transcripts
  • 3 Letters of Recommendation
  • Academic Statement of Purpose
  • Personal Statement
  • CV/Resume
Specialization Notes

Department of Electrical Engineering and Computer Science