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. et al. (2024) 'Robust low-cost drone detection and classification using convolutional neural networks in low SNR environments', IEEE Journal of Radio Frequency Identification, 8, pp. 821–830. doi: 10.1109/JRFID.2024.3487303.
• Lardos, A. et al. (2022) 'Computational literature-based discovery for natural products research : current state and future prospects', Frontiers in Bioinformatics, 2(827207). doi: 10.3389/fbinf.2022.827207.

Schriftliche Konferenzbeiträge, peer-reviewed

• Aghaebrahimian, A., Anisimova, M. and Gil, M. (2022) 'Ontology-aware biomedical relation extraction', in Sojka, P. et al. (eds) Text, Speech, and Dialogue. Cham: Springer, pp. 160–171. doi: 10.1007/978-3-031-16270-1_14.
• Tuggener, D. and Aghaebrahimian, A. (2021) 'The Sentence End and Punctuation Prediction in NLG text (SEPP-NLG) shared task 2021', in Proceedings of the Swiss Text Analytics Conference 2021. CEUR Workshop Proceedings. doi: 10.21256/zhaw-23258.
• Aghaebrahimian, A. and Cieliebak, M. (2020) 'Named entity disambiguation at scale', in Schilling, F.-P. and Stadelmann, T. (eds) Artificial Neural Networks in Pattern Recognition. Cham: Springer, pp. 102–110. doi: 10.1007/978-3-030-58309-5_8.
• Aghaebrahimian, A. and Cieliebak, M. (2019) 'Towards integration of statistical hypothesis tests into deep neural networks', in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, pp. 5551–5557. doi: 10.18653/v1/P19-1557.
• Aghaebrahimian, A., Ustaszewski, M. and Stauder, A. (2019) 'The TransBank Aligner : cross-sentence alignment with Deep Neural Networks', in Ekstein, K. (ed.) Text, Speech, and Dialogue. Cham: Springer, pp. 185–196. doi: 10.1007/978-3-030-27947-9_16.
• Aghaebrahimian, A. and Cieliebak, M. (2019) 'Hyperparameter tuning for deep learning in natural language processing', in 4th Swiss Text Analytics Conference (SwissText 2019), Winterthur, June 18-19 2019. Swisstext. doi: 10.21256/zhaw-18993.

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