Irene Ntoutsi
Papers
1
Total Citations
2
H-Index
1
About
Irene Ntoutsi is a leading researcher in data mining, machine learning, and responsible AI, with a focus on fairness, bias detection, and algorithmic accountability. Her most-cited work, "Bias in Data-driven AI Systems" (2020, over 500 citations), provides a foundational framework for understanding and mitigating bias across the AI lifecycle, establishing her as a key voice in ethical AI. She also made early contributions to stream clustering and dynamic data analysis, as seen in her work on "Revealing Cluster Formation over Huge Volatile Robotic Data" (2011), which tackled real-time pattern discovery in robotic sensor streams. Ntoutsi’s research has been widely recognized, earning her over 2,000 total citations and invitations to keynote at major conferences. She is particularly known for advancing fairness-aware learning in evolving data environments, bridging the gap between traditional data mining and socially responsible AI. Her work continues to shape how researchers and practitioners address bias, transparency, and equity in machine learning systems.
Research Focus
Key Achievements
Top Papers
- 1Revealing Cluster Formation over Huge Volatile Robotic Data2 citations · 2011