Dr. Ahmad Aghaebrahimian

Netzwerk

Mitglied in Netzwerken

Swiss Institute of Bioinformatics

Projekte

• Verbesserte Zugänglichkeit zu Informationen in Krankenhäusern durch den Einsatz von Large Language Models / Projektleiter:in / laufend
• Radio Signal Unsupervised and Transfer Learning / Teammitglied / abgeschlossen
• Verbesserung Large Language Models mit SNOMED CT für die Zusammenfassung mehrerer Patient:innen-Akten / Projektleiter:in / abgeschlossen
• Verbesserte Zugänglichkeit zu Informationen in Krankenhäusern durch den Einsatz von Large Language Models / Projektleiter:in / abgeschlossen
• AI for colorectal cancer: towards the improved CMS classification and interpretability / Teammitglied / abgeschlossen
• Inferring Ancestral Insertion and Deletion Events in Genomic Sequences / Teammitglied / abgeschlossen
• Computational Literature-based Discovery Methods / Teammitglied / abgeschlossen
• AuSuM – Automatic Supply Chain Monitoring / Stellv. Projektleiter:in / abgeschlossen

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, 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

Schriftliche Konferenzbeiträge, 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., 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
• 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

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