Dr. Ahmad Aghaebrahimian

Projects

• Advancing Information Accessibility in Hospitals Employing Large Language Models / Project leader / ongoing
• Radio Signal Unsupervised and Transfer Learning / Team member / completed
• Towards Enhancing Large Language Models with SNOMED CT for Multi-document Patient Records Summarization / Project leader / completed
• Boosting the Development of Plant Cell Cultures with Deep Learning Through Literature Mining / Project leader / completed
• AI for colorectal cancer: towards the improved CMS classification and interpretability / Team member / completed
• AuSuM – Automatic Supply Chain Monitoring / Deputy project leader / completed

Publications

Articles in scientific journal, peer-reviewed

• Glüge, S., Nyfeler, M., Aghaebrahimian, A., Ramagnano, N., & Schüpbach, C. (2024). Robust low-cost drone detection and classification using convolutional neural networks in low SNR environments. IEEE Journal of Radio Frequency Identification, 8, 821–830. https://doi.org/10.1109/JRFID.2024.3487303
• Lardos, A., Aghaebrahimian, A., Koroleva, A., Sidorova, J., Wolfram, E., Anisimova, M., & Gil, M. (2022). Computational literature-based discovery for natural products research : current state and future prospects. Frontiers in Bioinformatics, 2(827207). https://doi.org/10.3389/fbinf.2022.827207

Written conference contributions, peer-reviewed

• Aghaebrahimian, A., Anisimova, M., & Gil, M. (2022). Ontology-aware biomedical relation extraction [Conference paper]. In P. Sojka, A. Horák, I. Kopeček, & K. Pala (Eds.), Text, Speech, and Dialogue (pp. 160–171). Springer. https://doi.org/10.1007/978-3-031-16270-1_14
• Tuggener, D., & Aghaebrahimian, A. (2021, September 29). The Sentence End and Punctuation Prediction in NLG text (SEPP-NLG) shared task 2021. Proceedings of the Swiss Text Analytics Conference 2021. https://doi.org/10.21256/zhaw-23258
• Aghaebrahimian, A., & Cieliebak, M. (2020). Named entity disambiguation at scale [Conference paper]. In F.-P. Schilling & T. Stadelmann (Eds.), Artificial Neural Networks in Pattern Recognition (pp. 102–110). Springer. https://doi.org/10.1007/978-3-030-58309-5_8
• Aghaebrahimian, A., & Cieliebak, M. (2019). Hyperparameter tuning for deep learning in natural language processing. 4th Swiss Text Analytics Conference (SwissText 2019), Winterthur, June 18-19 2019. https://doi.org/10.21256/zhaw-18993
• Aghaebrahimian, A., Ustaszewski, M., & Stauder, A. (2019). The TransBank Aligner : cross-sentence alignment with Deep Neural Networks [Conference paper]. In K. Ekstein (Ed.), Text, Speech, and Dialogue (pp. 185–196). Springer. https://doi.org/10.1007/978-3-030-27947-9_16
• Aghaebrahimian, A., & Cieliebak, M. (2019). Towards integration of statistical hypothesis tests into deep neural networks [Conference paper]. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 5551–5557. https://doi.org/10.18653/v1/P19-1557

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