Prof. Dr. Andreas M. Kist
Juniorprofessur für Artificial Intelligence in Communication Disorders
Prof. Dr. Andreas M. Kist
Juniorprofessur für Artificial Intelligence in Communication Disorders
My group mines artificial intelligence methodologies for efficiency and robustness to allow eventual clinical applicability.
We focus on the analysis and integration of biomedical imaging and multisensory data to compute quantitative clinically relevant features.
Research Projects
- Diagnostik und Therapieverlauf durch den Einsatz von KI-Methoden
- KI-basierte multimodale Datenerhebung, insbesondere von Audio- und Bildmaterial
- Optimierung und Generalisierung von neuronalen Netzen für die erfolgreiche Anwendung in der Klinik
- Erstellung von Benchmark-Datensätzen für umfassende Reproduzierbarkeit
- Neuronale Architekturoptimierung für die Anwendung auf Mikrocontrollern
- Hardware- und Softwareseitige Implementierung von Hardwarebeschleunigern für die effiziente Datenverarbeitung
- Architekturoptimierung für den Einsatz in der Medizin
- Maximierung von Robustheit und Generalität neuronaler Netze
- Balancierte neuronale Netze durch ganzheitliche Ressourcenoptimierung
- Entwicklung von Software für effizientes überwachtes Lernen
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Do stability of hippocampal neuronal excitatory synaptic connectivity and representations support spatial learning?
(Third Party Funds Single)
Project leader:
Term: 1. August 2025 - 31. July 2028
Funding source: DFG-Einzelförderung / Sachbeihilfe (EIN-SBH)Hippocampal pyramidal neurons encode spatial locations through localized firing patterns, or place cells. Studies in humans and animals have shown a critical role for the hippocampus in spatial and episodic memory. Several theories have sought to explain how the hippocampus supports these functions and have considered place cells as basic substrates of long-term spatial memory. In many such frameworks, a central tenet is that long-term spatial memory arises from ensembles of cells that retain their spatial coding properties over time periods relevant to long-term memory. However, hippocampal spatial representations exhibit a surprising level of instability, or drift, which seems counterintuitive for a brain region important for memory formation. A few hypotheses exist on the function of this phenomenon, but the cellular and circuit mechanisms underlying hippocampal representational drift representations are completely unknown. By using two-photon time-lapse imaging to track simultaneously excitatory structural plasticity and activity patterns of the same pyramidal neurons over several days in the hippocampus of live mice, we want to shed light on the link between the stability connectivity and the drift of hippocampal representations. Moreover, we will study the relationship between structural plasticity, representation turnover, and learning by using a behavioral learning task, concomitant to imaging, and by perturbing the activity patterns of hippocampal dorsal CA1 pyramidal neurons by increasing local inhibition. In parallel, - and to increase the efficiency and reliability of our data analysis – we will develop a method based on machine and deep learning to consistently and automatically track dendritic spines in two-photon image time lapses and to match these to the activity of single pyramidal neurons in hippocampal dorsal CA1.
2026
- Neubig, L., Larsen, D., Ikuma, T., Kopp, M., Kunduk, M., & Kist, A. (2026). Markerless Tracking-Based Registration for Medical Image Motion Correction. In Lina Felsner, Thomas Küstner, Andreas Maier, Chen Qin, Seyed-Ahmad Ahmadi, Anees Kazi, Xiaoling Hu (Eds.), Lecture Notes in Computer Science (pp. 34-43). Daejeon, KOR: Springer Science and Business Media Deutschland GmbH.
- Zimmermann, S., Groh, R., & Kist, A. (2026). Elevating AI on the Edge: A Demonstration of MIMaaS (Machine Intelligence with Microcontroller-as-a-Service). In Sven Koenig, Chad Jenkins, Matthew E. Taylor (Eds.), Proceedings of the AAAI Conference on Artificial Intelligence (pp. 41751-41753). Singapore: Association for the Advancement of Artificial Intelligence.
2025
- Arjomandi, J., Neubig, L., & Kist, A. (2025). LLM-driven Baselines for Medical Image Segmentation: A Systematic Analysis. In Christoph Palm, Katharina Breininger, Thomas Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Thomas M. Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2025. Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025 (pp. 50-56). Regensburg, DE: Cham: Springer.
- Chao, A., Martignetti, L., Groh, R., Kist, A., & Li-Jessen, N.Y. (2025). An mHealth App and System Architecture for Respiratory Disease Management: Design Principles, Tool Development, and Pilot Usability Study. JMIR Formative Research, 9. https://doi.org/10.2196/73584
- Dendorfer, S., & Kist, A. (2025). Population-based guiding for evolutionary neural architecture search. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-25840-5
- Dörrich, M., Balk, M., Heusinger, T., Beyer, S., Mirbagheri, M., Fischer, D.J.,... Kist, A. (2025). A multimodal dataset for precision oncology in head and neck cancer. Nature Communications, 16(1). https://doi.org/10.1038/s41467-025-62386-6
- Hauser, S., Kist, A., Döllinger, M., & Kniesburges, S. (2025). Implicit neural representations for laryngeal aerodynamics. Physics of Fluids, 37(8). https://doi.org/10.1063/5.0267402
- Kist, A., Razi, S., Groh, R., Gritsch, F., & Schützenberger, A. (2025). Predicting semantic segmentation quality in laryngeal endoscopy images. PLoS ONE, 20(7 July). https://doi.org/10.1371/journal.pone.0314573
- Neubig, L., Larsen, D., Kunduk, M., & Kist, A. (2025). Unstructured electronic health records of dysphagic patients analyzed by large language models. IEEE Journal of Translational Engineering in Health and Medicine. https://doi.org/10.1109/JTEHM.2025.3571255
2024
- Darvish, M., & Kist, A. (2024). A Generative Method for a Laryngeal Biosignal. Journal of Voice. https://doi.org/10.1016/j.jvoice.2024.01.016
- Fernholz, M.H., Guggiana Nilo, D.A., Bonhoeffer, T., & Kist, A. (2024). DeepD3, an open framework for automated quantification of dendritic spines. PLoS Computational Biology, 20(2). https://doi.org/10.1371/journal.pcbi.1011774
- Groh, R., Goes, N., & Kist, A. (2024). SpokeN-100: A Cross-Lingual Benchmarking Dataset for The Classification of Spoken Numbers in Different Languages. In Proceedings of the tinyML Research Symposium 2024. Burlingame, CA, US.
- Groh, R., Li, J.Y., Li-Jessen, N.Y., & Kist, A. (2024). ANNOTE: Annotation of time-series events. Software Impacts, 21. https://doi.org/10.1016/j.simpa.2024.100679
- Hauser, S.L., Brosig, J., Murthy, B., Attardo, A., & Kist, A. (2024). Implicit neural representations in light microscopy. Biomedical Optics Express, 15(4), 2175-2186. https://doi.org/10.1364/BOE.515517
- Hecht, M., Frey, B., Gaipl, U., Tianyu, X., Eckstein, M., Donaubauer, A.-J.,... Kist, A. (2024). Machine Learning-assisted immunophenotyping of peripheral blood identifies innate immune cells as best predictor of response to induction chemo-immunotherapy in head and neck squamous cell carcinoma – knowledge obtained from the CheckRad-CD8 trial. Neoplasia, 49. https://doi.org/10.1016/j.neo.2023.100953
- Kist, A., & Döllinger, M. (2024). Have We Solved Glottis Segmentation? Review and Commentary. Journal of Voice. https://doi.org/10.1016/j.jvoice.2024.11.037
- Lojo Rodríguez, M.B., Lopes Borges, G., López-Brea García, M., Schützenberger, A., & Kist, A. (2024). Neural Radiance Fields for 3D Reconstruction in Monoscopic Laryngeal Endoscopy. In 2024 IEEE International Symposium on Biomedical Imaging (ISBI). Athen, GR: Institute of Electrical and Electronics Engineers, Inc..
- Pava, M.Á., Groh, R., & Kist, A. (2024). Sequence Alignment-based Similarity Metric in Evolutionary Neural Architecture Search. In Katharina Eggensperger, Roman Garnett, Joaquin Vanschoren, Marius Lindauer, Jacob R. Gardner (Eds.), Proceedings of Machine Learning Research. Paris, FR: ML Research Press.
2023
- Csűry, T.D., Csűry, A.Z., Balk, M., Kist, A., Rupp, R., Müller, S.K.,... Gostian, A.-O. (2023). The modified Polsby–Popper score, a novel quantitative histomorphological biomarker and its potential to predict lymph node positivity and cancer-specific survival in oral tongue squamous cell carcinoma. Cancer Medicine. https://doi.org/10.1002/cam4.6824
- Dörrich, M., Fan, M., & Kist, A. (2023). Impact of Mixed Precision Techniques on Training and Inference Efficiency of Deep Neural Networks. IEEE Access, 11, 57627-57634. https://doi.org/10.1109/ACCESS.2023.3284388
- Dörrich, M., Hecht, M., Fietkau, R., Hartmann, A., Iro, H., Gostian, A.-O.,... Kist, A. (2023). Explainable convolutional neural networks for assessing head and neck cancer histopathology. Diagnostic Pathology, 18(1). https://doi.org/10.1186/s13000-023-01407-8
- Groh, R., & Kist, A. (2023). End-To-end Evolutionary Neural Architecture Search for Microcontroller Units. In 2023 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2023. Berlin, DEU: Institute of Electrical and Electronics Engineers Inc..
- Gruenerbel, L., Heinrich, F., Böhlhoff-Martin, J., Röper, L., Machens, H.G., Gruenerbel, A.,... Steinbacher, L. (2023). Wearable Prophylaxis Tool for AI-Driven Identification of Early Warning Patterns of Pressure Ulcers. Bioengineering, 10(10). https://doi.org/10.3390/bioengineering10101125
- Kist, A. (2023). Artificial Intelligence in Laryngeal Endoscopy Künstliche Intelligenz in der laryngealen Endoskopie. Sprache, Stimme, Gehör, 47(3), 134-138. https://doi.org/10.1055/a-2089-5741
- Kruse, E., Döllinger, M., Schützenberger, A., & Kist, A. (2023). GlottisNetV2: Temporal Glottal Midline Detection using Deep Convolutional Neural Networks. IEEE Journal of Translational Engineering in Health and Medicine, 1-1. https://doi.org/10.1109/JTEHM.2023.3237859
- Larsen, D., Ikuma, T., Neubig, L., Kist, A., Leonard, R., McWhorter, A.J., & Kunduk, M. (2023). Pixel-Based Swallow Measurements: Correcting Nonsquare Pixels. Journal of Speech Language and Hearing Research, 66(2), 565-572. https://doi.org/10.1044/2022_JSLHR-22-00306
- Neubig, L., & Kist, A. (2023). Dataset Pruning using Evolutionary Optimization. In Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 134-139). Braunschweig, DEU: Springer Science and Business Media Deutschland GmbH.
- Neubig, L., & Kist, A. (2023). Evolutionary Normalization Optimization Boosts Semantic Segmentation Network Performance. In Hayit Greenspan, Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan, Tanveer Syeda-Mahmood, Russell Taylor (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 703-712). Vancouver, BC, CAN: Springer Science and Business Media Deutschland GmbH.
- Sun, Y., & Kist, A. (2023). Compact Convolutional Transformers on Edge TPUs. In Proceedings of the Bildverarbeitung für die Medizin Workshop, BVM 2023 (pp. 141-146). Springer Science and Business Media Deutschland GmbH.
- Wölfl, A.-M., Schützenberger, A., Breininger, K., & Kist, A. (2023). Towards image-based laryngeal videostroboscopy using deep learning-enabled compressed sensing. Biomedical Signal Processing and Control, 86, Part C. https://doi.org/10.1016/j.bspc.2023.105335
2022
- Dürr, S., Schützenberger, A., Kist, A., Semmler, M., Schraut, T., Arias Vergara, T., & Döllinger, M. (2022). High-speed video endoscopy to improve the diagnosis of voice disorders.
- Groh, R., Dürr, S., Schützenberger, A., Semmler, M., & Kist, A. (2022). Long-term performance assessment of fully automatic biomedical glottis segmentation at the point of care. PLoS ONE, 17(9), e0266989-. https://doi.org/10.1371/journal.pone.0266989
- Groh, R., Lei, Z., Martignetti, L., Li-Jessen, N.Y.K., & Kist, A. (2022). Efficient and Explainable Deep Neural Networks for Airway Symptom Detection in Support of Wearable Health Technology. Advanced Intelligent Systems. https://doi.org/10.1002/aisy.202100284
- Kist, A., Breininger, K., Dörrich, M., Dürr, S., Schützenberger, A., & Semmler, M. (2022). A single latent channel is sufficient for biomedical glottis segmentation. Scientific Reports, 12(1), 14292-. https://doi.org/10.1038/s41598-022-17764-1
- Neubig, L., Groh, R., Kunduk, M., Larsen, D., Leonard, R., & Kist, A. (2022). Efficient Patient Orientation Detection in Videofluoroscopy Swallowing Studies. In Klaus Maier-Hein, Thomas M. Deserno, Heinz Handels, Andreas Maier, Christoph Palm, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 129-134). Heidelberg, DEU: Springer Science and Business Media Deutschland GmbH.
- Schleiss, J., Hense, J., Kist, A., Schlingensiepen, J., & Stober, S. (2022). TEACHING AI COMPETENCIES IN ENGINEERING USING PROJECTS AND OPEN EDUCATIONAL RESOURCES. In Hannu-Matti Jarvinen, Santiago Silvestre, Ariadna Llorens, Balazs Vince Nagy (Eds.), SEFI 2022 - 50th Annual Conference of the European Society for Engineering Education, Proceedings (pp. 1592-1600). Barcelona, ES: European Society for Engineering Education (SEFI).
2021
- Kist, A., Zilker, J., Döllinger, M., & Semmler, M. (2021). Feature-based image registration in structured light endoscopy. In Proceedings of Machine Learning Research (pp. 369-383). Lübeck, DE.
- Kniesburges, S., Schlegel, P., Peters, G., Westphalen, C., Jakubaß, B., Veltrup, R.,... Echternach, M. (2021). Effects of surgical masks on aerosol dispersion in professional singing. Journal of Exposure Science and Environmental Epidemiology. https://doi.org/10.1038/s41370-021-00385-7
- Markov, D.A., Petrucco, L., Kist, A., & Portugues, R. (2021). A cerebellar internal model calibrates a feedback controller involved in sensorimotor control. Nature Communications, 12(1). https://doi.org/10.1038/s41467-021-26988-0