Joscha Cüppers is a PhD student who is working on novel methods for mining patterns from data. He is particularly interested in developing methods for discovering interactions and abstractions from sequential data.
Joscha obtained his Bachelor of Science in Computer Science in 2016 from Ulm University and his Master of Science from Saarland University in 2019. He joined the EDA group in 2019 to write his Master's thesis and started his PhD with us in 2020.
2025 | |
Succinct Interaction-Aware Explanations. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2025. (19% acceptance rate) |
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2024 | |
Discovering Sequential Patterns with Predictable Inter-Event Delays. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2024. (23.8% acceptance rate) |
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FlowChronicle: Synthetic Network Flow Generation through Pattern Set Mining. In: Proceedings of the ACM International Conference on Emerging Networking Experiments and Technologies (CoNEXT), ACM, 2024. |
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Causal Discovery from Event Sequences by Local Cause-Effect Attribution. In: Proceedings of Neural Information Processing Systems (NeurIPS), PMRL, 2024. (25.8% acceptance rate) |
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2023 | |
Below the Surface: Summarizing Event Sequences with Generalized Sequential Patterns. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2023. (22.1% acceptance rate) |
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2022 | |
Omen: Discovering Sequential Patterns with Reliable Prediction Delays. Knowledge and Information Systems vol.64(4), pp 1013-1045, Springer, 2022. (IF 2.822) |
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2020 | |
Just Wait For It... Mining Sequential Patterns with Reliable Prediction Delays. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'20), IEEE, 2020. (full paper, 9.8% acceptance rate; overall 19.7%) (invited for the KAIS Special Issue on the Best of IEEE ICDM 2020) |