Leitung von Interpretierbare KI für die Analyse von Gene-Expressionsdaten gefördert von Bundesministerium für Wirtschaft und Klimaschutz 2022 - 2025 Kl-unterstütze Optimierung des Einsatzes von NIR/MIR-Sensoren in der Landwirtschaft gefördert von Bundesanstalt für Landwirtschaft und Ernährung 2021 - 2024 Nachwuchsforschergruppe MaLeKITA Maschinelles Lernen und KI in Theorie und Anwendungen, MaLeKITA Anwendungen Theorie gefördert von Sächsische Aufbaubank 2020 - 2022
ausgewählte Veröffentlichungen Journalartikel Multi-proximity based embedding scheme for learning vector quantization-based classification of biochemical structured data. Neurocomputing. 126632. 2023 Alignment-free sequence comparison: A systematic survey from a machine learning perspective. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 119-135. 2022 Learning vector quantization as an interpretable classifier for the detection of SARS-CoV-2 types based on their RNA sequences. Neural Computing and Applications. 2021 The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers. Entropy. 1357. 2021 Virxicon: a lexicon of viral sequences. Bioinformatics. 5507-5513. 2021 Konferenzpaper Biologically-Informed Shallow Classification Learning Integrating Pathway Knowledge. Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOINFORMATICS. 357-367. 2024 Efficient Representation of Biochemical Structures for Supervised and Unsupervised Machine Learning Models Using Multi-Sensoric Embeddings. Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOINFORMATICS. 59-69. 2023 Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection. ESANN 2023 Proceedings. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 65-70. 2023 Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features. ESANN 2022 Proceedings. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 445-450. 2022
Präsentationen Vortrag Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features, Vortragende, während 30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 2022 Efficient molecule classification based on multiple graph kernels using a sensoric response principle and interpretable machine learning models, Vortragende, während German Conference on Bioinformatics 2022 2022
hat Teilnehmerrolle 14th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization 2022