INF 7 Institut für Datensicherheit
| Gebäude Carl-Wery-Str. 18, Zimmer CWS18/2816 | |
| +49 89 6004-7421 | |
| arjun.roy@unibw.de |
Arjun Roy M.Tech.
Arjun Roy, research assistant at the Chair of Open Source Intelligence, is a seasoned researcher with over six years of dedicated experience in the dynamic field of machine learning. Currently, he is affiliated with the Research Institute CODE (Cyber Defence and Smart Data) at Universität der Bundeswehr München, where he is actively engaged in the AIML lab, working on the EU project MAMMOth.
He is pursuing my PhD in Machine Learning at the Department of Mathematics & Computer Science, Institute of Computer Science, Freie Universität Berlin, under the guidance of Prof. Dr Eirini Ntoutsi. His expertise spans a wide array of domains within Machine Learning, including FairML, Multi-task Learning, Robustness and Privacy in ML, Multi-objective Learning, Deep Reinforcement Learning, Multi-modal Learning, Federated Learning, and Natural Language Processing. Arjun thrives on exploring the intricate nuances of these domains and pushing the boundaries of innovation to develop robust and scalable solutions.
He is pursuing my PhD in Machine Learning at the Department of Mathematics & Computer Science, Institute of Computer Science, Freie Universität Berlin, under the guidance of Prof. Dr Eirini Ntoutsi. His expertise spans a wide array of domains within Machine Learning, including FairML, Multi-task Learning, Robustness and Privacy in ML, Multi-objective Learning, Deep Reinforcement Learning, Multi-modal Learning, Federated Learning, and Natural Language Processing. Arjun thrives on exploring the intricate nuances of these domains and pushing the boundaries of innovation to develop robust and scalable solutions.
Recently Published Works:
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FairBranch: Mitigating Bias Transfer in Fair Multi-task Learning; Arjun Roy, Christos Koutlis, Symeon Papadopoulos, Eirini Ntoutsi; International Joint Conference on Neural Networks (IJCNN), 2024. [paper]
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Adversarial Robustness of VAEs across Intersectional Subgroups; Chethan K. Ramanaik, Arjun Roy, Eirini Ntoutsi; Workshop on Bias and Fairness in AI at ECML PKDD, 2024. [preprint]
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Synthetic Tabular Data Generation for Class Imbalance and Fairness: A Comparative Study; Emmanouil Panagiotou, Arjun Roy, Eirini Ntoutsi; Workshop on Bias and Fairness in AI at ECML PKDD, 2024. [preprint]
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Exploring Fusion Techniques in Multimodal AI-Based Recruitment: Insights from FairCVdb; Swati Swati, Arjun Roy, Eirini Ntoutsi; European Workshop on Algorithmic Fairness, 2024. [preprint]
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Multi-dimensional discrimination in Law and Machine Learning - A comparative overview; Arjun Roy, Jan Horstmann, Eirini Ntoutsi; ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2023. [paper]
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Multi-fairness under class-imbalance; Arjun Roy, Vasileios Iosifidis, Eirini Ntoutsi; International Conference on Discovery Science (DS)2022. [paper] [video]
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Learning to Teach Fairness-aware Deep Multi-task Learning; Arjun Roy, Eirini Ntoutsi; European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), 2022. [paper] [code] [video]
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A survey on datasets for fairness-aware machine learning; Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi; Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, 2022. [paper] [code]
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Exploiting stance hierarchies for cost-sensitive stance detection of Web documents; Arjun Roy, Pavlos Fafalios, Asif Ekbal, Xiaofei Zhu, Stefan Dietze; Journal of Intelligent Information Systems (JIIS), Springer, 2022. [paper] [code]
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Parity-based Cumulative Fairness-aware Boosting; Vasileios Iosifidis, Arjun Roy, Eirini Ntoutsi; Knowledge and Information Systems (KAIS), Springer, 2022. [paper] [code]
Postal address:
Universität der Bundeswehr München
Forschungsinstitut CODE
Professur für Open Source Intelligence
Werner-Heisenberg-Weg 39
85577 Neubiberg
Visitor address:
Forschungsinstitut CODE
Carl-Wery-Straße 18-22
81739 München