| 2025 | CSEDU | Position Paper: Computer Supported Education vs. Education Supported Computing - On the Problem of Informed Decision Making of Appropriate Data Analytics Method. | Daniyal Kazempour, Christiane Attig, Peer Krger, Muhammad Aammar Tufail, Daniela E. Winkler, Claudius Zelenka |
| 2024 | CSEDU | What Will I Need this for Later? Towards a Platform for the Discovery of Intra and Inter-Module Content Relations. | Lisa Anders, Daniyal Kazempour, Peer Krger |
| 2024 | EDBT | The Missing Link? On the In-Between Instance Detection Task. | Daniyal Kazempour, Claudius Zelenka, Peer Krger |
| 2024 | ICDM | Do good scores imply good embeddings? On the necessity of inspecting manifold learning evaluation results by multiple criteria. | Daniyal Kazempour, Claudius Zelenka, Atakan Kara, Andreas Lohrer, Peer Krger |
| 2024 | ICDM | Not the same, yet similar? - On commonalities and differences between VQPCA and ORCLUS. | Daniyal Kazempour, Claudius Zelenka, Artjom Mukhamedov, Peer Krger |
| 2024 | MDM | Data Fusion Between Land and Sea: Multi-Isotope Fingerprints of Viking Animals and Modern Plants. | Andrea Ghring, Mirjam Bayer, Daniyal Kazempour, Sweety Mohanty, Claudius Zelenka |
| 2020 | DASFAA | AMTICS: Aligning Micro-clusters to Identify Cluster Structures. | Florian Richter, Yifeng Lu, Daniyal Kazempour, Thomas Seidl |
| 2020 | ICDM | I fold you so! An internal evaluation measure for arbitrary oriented subspace clustering. | Daniyal Kazempour, Anna Beer, Peer Krger, Thomas Seidl |
| 2020 | ICDM | Towards an Internal Evaluation Measure for Arbitrarily Oriented Subspace Clustering. | Daniyal Kazempour, Peer Krger, Thomas Seidl |
| 2020 | ICDM | You see a set of wagons - I see one train: Towards a unified view of local and global arbitrarily oriented subspace clusters. | Daniyal Kazempour, Long Mathias Yan, Peer Krger, Thomas Seidl |
| 2020 | PAKDD | Detecting Arbitrarily Oriented Subspace Clusters in Data Streams Using Hough Transform. | Felix Borutta, Daniyal Kazempour, Felix Mathy, Peer Krger, Thomas Seidl |
| 2019 | BTW | DICE: Density-based Interactive Clustering and Exploration. | Daniyal Kazempour, Maksim Kazakov, Peer Krger, Thomas Seidl |
| 2019 | EDBT | Rock - Let the points roam to their clusters themselves. | Anna Beer, Daniyal Kazempour, Thomas Seidl |
| 2019 | EDBT | Insights into a running clockwork: On interactive process-aware clustering. | Daniyal Kazempour, Thomas Seidl |
| 2019 | EDBT | A Galaxy of Correlations. | Daniyal Kazempour, Lisa Krombholz, Peer Krger, Thomas Seidl |
| 2019 | HCI | Human Learning in Data Science. | Anna Beer, Daniyal Kazempour, Marcel Baur, Thomas Seidl |
| 2019 | HCI | Data on RAILs: On Interactive Generation of Artificial Linear Correlated Data. | Daniyal Kazempour, Anna Beer, Thomas Seidl |
| 2019 | SISAP | SIDEKICK: Linear Correlation Clustering with Supervised Background Knowledge. | Maximilian Archimedes Xaver Hnemrder, Daniyal Kazempour, Peer Krger, Thomas Seidl |
| 2019 | SISAP | On coMADs and Principal Component Analysis. | Daniyal Kazempour, Max Hnemrder, Thomas Seidl |
| 2019 | SSDBM | LUCK- Linear Correlation Clustering Using Cluster Algorithms and a kNN based Distance Function. | Anna Beer, Daniyal Kazempour, Lisa Stephan, Thomas Seidl |
| 2019 | SSDBM | On systematic hyperparameter analysis through the example of subspace clustering. | Daniyal Kazempour, Thomas Seidl |
| 2019 | SSDBM | Detecting Global Periodic Correlated Clusters in Event Series based on Parameter Space Transform. | Daniyal Kazempour, Kilian Emmerig, Peer Krger, Thomas Seidl |
| 2018 | SISAP | D-MASC: A Novel Search Strategy for Detecting Regions of Interest in Linear Parameter Space. | Daniyal Kazempour, Kevin Bein, Peer Krger, Thomas Seidl |
| 2018 | SSDBM | PARADISO: an interactive approach of parameter selection for the mean shift algorithm. | Daniyal Kazempour, Anna Beer, Johannes-Y. Lohrer, Daniel Kaltenthaler, Thomas Seidl |
| 2017 | SSDBM | Detecting Global Hyperparaboloid Correlated Clusters Based on Hough Transform. | Daniyal Kazempour, Markus Mauder, Peer Krger, Thomas Seidl |