Publications

2025

• A Deep Latent Factor Graph Clustering with Fairness-Utility Trade-off Perspective (accepted) Siamak Ghodsi, Amjad Seyedi, Tai Le Quy, Fariba Karimi, Eirini Ntoutsi
  IEEE Big Data

• TABFAIRGDT - A Fast Fair Tabular Data Generator using Autoregressive Decision Trees (accepted) Emmanouil Panagiotou, Benoît Ronval, Arjun Roy, Ludwig Bothmann, Bernd Bischl, Siegfried Nijssen, Eirini Ntoutsi
  IEEE International Conference on Data Mining (ICDM)

• MMM-fair An Interactive Toolkit for Exploring and Operationalizing Multi-Fairness Trade-offs (accepted) Swati Swati, Arjun Roy, Emmanouil Panagiotou, Eirini Ntoutsi
  ACM Conference on Information and Knowledge Management (CIKM)

• The Multifaced Nature of Bias in AI - Impact on Model Generalization, Robustness, and Fairness Eirini Ntoutsi
  Schäffer, B., Lieder, F.R. (eds) Maschinen wie wir?. Springer Gabler, Wiesbaden

• Generative AI-augmented offshore jacket design: Integrated approach for mixed tabular data generation under scarcity and imbalance (accepted) Emmanouil Panagiotou, Han Qian, Steffen Marx, Eirini Ntoutsi
  Automation in Construction Journal

• Achieving Socio-Economic Parity through the Lens of EU AI Act (accepted) Arjun Roy, Stavroula Rizuo, Symeon Papadopoulos, Eirini Ntoutsi
  ACM Conference on Fairness, Accountability, and Transparency (FAccT) [local copy]

• Mitigating Semantic Drift: Evaluating LLMs Efficacy in Psychotherapy through In-context Conversational Dialogue Summarization Leveraging MITI Code (accepted) Vivek Kumar, Pushpraj Singh, Eirini Ntoutsi 
  International Joint Conference on Neural Networks (IJCNN)

• Ziqi Xu, Sevvandi Kandanaarachchi, Cheng Soon Ong, Eirini Ntoutsi. Fairness Evaluation with Item Response Theory (accepted). The Web Conference (WWW 2025).

2024

• Panagiotou Emmanouil, Heurich Manuel, Landgraf Tim, Ntoutsi Eirini. TABCF: Counterfactual Explanations for Tabular Data Using a Transformer-Based VAE. 5th ACM International Conference on AI in Finance.
• Ramanaik Chethan Krishnamurthy, Arjun Roy, and Eirini Ntoutsi. Adversarial Robustness of VAEs across Intersectional Subgroups. 4th BIAS workshop, co-located with ECML PKDD 2024.
• Panagiotou Emmanouil, Arjun Roy, and Eirini Ntoutsi, Synthetic Tabular Data Generation for Class Imbalance and Fairness: A Comparative Study. 4th BIAS workshop, co-located with ECML PKDD 2024.
• Julia Huuk, Berend Denkena, Abheek Dhingra, Eirini Ntoutsi, Shape error prediction in 5-axis machining using graph neural networks. 18th CIRP ICME Conference on Intelligent Computation in Manufacturing Engineering. (accepted)
• Yi Cai, Arthur Zimek, Eirini Ntoutsi, Gerhard Wunder, Transparent Neighborhood Approximation for Text Classifier Explanation by Probability-based Editing. 11th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2024) (accepted)
• Swati Swati, Arjun Roy, Eirini Ntoutsi, Exploring Fusion Techniques in Multimodal AI-Based Recruitment: Insights from FairCVdb. Proceedings of the 2nd European Workshop on Algorithmic Fairness (EWAF’24) [local copy] (accepted).
• Vivek Kumar, Pushpraj Singh Rajawat, Giacomo Medda, Eirini Ntoutsi and Diego Reforgiato Recupero:  Unlocking LLMs Capabilities: Addressing Scarce Data and Inherent Bias Challenges in Mental Health and Therapeutic Counselling, International Conference on Natural Language Processing and Artificial Intelligence for Cyber Security (NLPAICS 2024) (accepted).
• Qian, Han, Emmanouil Panagiotou, Mengyan Peng, Eirini Ntoutsi, Chongjie Kang, and Steffen Marx. "A novel dataset and feature selection for data-driven conceptual design of offshore jacket substructures." Ocean Engineering 303 (2024): 117679. [local copy].
• Arjun Roy, Christos Koutlis, Symeon Papadopoulos, Eirini Ntoutsi, FairBranch: Mitigating Bias Transfer in Fair Multi-task Learning, International Joint Conference on Neural Networks (IJCNN)  (accepted).

• Siamak Ghodsi, Seyed Amjad Seyedi, Eirini Ntoutsi, Towards Cohesion-Fairness Harmony - Contrastive Regularization in Individual Fair Graph Clustering,  28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) [local copy].

2023

• Simone Fabbrizzi, Xuan Zhao, Emmanouil Krasanakis, Symeon Papadopoulos, Eirini Ntoutsi, Studying Bias in Visual Features through the Lens of Optimal Transport, 
  ECML-PKDD 2023 DAMI journal track [local copy].

• Vasilis Gkolemis, Theodore Dalamagas, Eirini Ntoutsi, Christos Diou, RHALE, Robust and Heterogeneity-aware Accumulated Local Effects,  26th European Conference on Artificial Intelligence (ECAI 2023) [local copy].

• Emmanouil Panagiotou, Eirini Ntoutsi, Learning impartial policies for sequential counterfactual explanations using Deep Reinforcement Learning, DynXAI workshop, co-located with ECML PKDD 2023 [local copy].

• Vasilis Gkolemis, Theodore Dalamagas, Eirini Ntoutsi, Christos Diou, Regionally Additive Models Explainable-by-design models minimizing feature interactions, XAI-uncertainty workshop, co-located with ECML PKDD 2023 [local copy].

• Siamak Ghodsi, Eirini Ntoutsi, Affinity Clustering Framework for Data Debiasing using Pairwise Distribution Discrepancy,  European Workshop on Algorithmic Fairness (EWAF’23), Winterthur, Switzerland.

• Emmanouil Panagiotou, Han Qian, Mareile Wynants, Anton Kriese, Steffen Marx, Eirini Ntoutsi, Explainable AI-based Generation of Offshore Substructure Designs, The 33rd International Ocean and Polar Engineering Conference (ISOPE-2023).

• Arjun Roy, Jan Horstmann, Eirini Ntoutsi, Multi-dimensional discrimination in Law and Machine Learning - A comparative overview,  ACM Conference on Fairness, Accountability, and Transparency 2023 (ACM FAccT 2023) [local copy] [video].

• Tai Le Quy, Gunnar Friege, Eirini Ntoutsi, Multi-fair capacitated students-topics grouping problem, The 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2023)
  [local copy] [ppt] [video].

• Tai Le Quy, Gunnar Friege, Eirini Ntoutsi, A review of clustering models in educational data science towards fairness-aware learning,  Peña-Ayala, A. (eds) Educational Data Science: Essentials, Approaches, and Tendencies. Big Data Management. Springer, Singapore.

• Vasileios Iosifidis, Symeon Papadopoulos, Bodo Rosenhahn, Eirini Ntoutsi, AdaCC cumulative cost-sensitive boosting for imbalanced classification, Knowledge and Information Systems (KAIS)
  [local copy] [code].

2022

• Emmanouil Panagiotou, Multi-objective substructure generation, The 18th EAWE PhD Seminar.

• Yi Cai, Arthur Zimek, Gerhard Wunder, Eirini Ntoutsi, Power of Explanations - Towards automatic debiasing in hate speech detection,  9th IEEE International Conference on Data Science and Advanced Analytics (DSAA) [local copy] [code].

• Tai Le Quy, Thi Huyen Nguyen, Gunnar Friege, Eirini Ntoutsi, Evaluation of group fairness measures in student performance prediction problems, SoGood 2022 – 7th Workshop on Data Science for Social Good@ECML/PKDD 2022, [local copy] [code] [ppt] [video].

• Simone Fabrizzi, Symeon Papadopoulos, Eirini Ntoutsi, Yannis Kompatsiaris, A survey on bias in visual datasets,  Computer Vision and Image Understanding (CVIU) journal
  [local copy].

• Arjun Roy, Vasileios Iosifidis, Eirini Ntoutsi, Multi-fairness under class-imbalance, Discovery Science (DS)2022, [local copy] [video].

• Vasileios Iosifidis, Arjun Roy, Eirini Ntoutsi, Parity-based Cumulative Fairness-aware Boosting,  Knowledge and Information Systems (KAIS)
  [local copy] [code].

• Arjun Roy, Eirini Ntoutsi, Learning to Teach Fairness-aware Deep Multi-task Learning, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), 2022, [local copy] [code].

• Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi, A survey on datasets for fairness-aware machine learning, Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, 2022, [local copy] [code].

Before 2022

• Eine Liste unserer bisher erschienenen Publikationen finden Sie hier.