Data Science
Publications
LongEval at CLEF 2025: Longitudinal Evaluation of IR Model Performance Matteo Cancellieri , Alaa El-Ebshihy, Tobias Fink, Petra Galuscakova, Gabriela Gonzalez-Saez, Lorraine Goeuriot, David Iommi, Juri Keller, Petr Knoth , Philippe Mulhem ,Florina Piroi, David Pride , and Philipp Schaer (UPCOMING)
Benchmark Creation for Narrative Knowledge Delta Extraction Tasks: Can LLMs Help?. Alaa El-Ebshihy, Annisa Maulida Ningtyas, Florina Piroi and Andreas Rauber (UPCOMING, ECIR 2025)
Alkhalifa, R., Borkakoty, H., Deveaud, R., El-Ebshihy, A., Espinosa-Anke, L., Fink, T., Gonzalez-Saez, G., Galuščáková, P., Goeuriot, L., Iommi, D., Liakata, M., Madabushi, H.T., Medina-Alias, P., Mulhem, P., Piroi, F., Popel, M., Servan, C. and Zubiaga, A., 2024. LongEval: Longitudinal Evaluation of Model Performance at CLEF 2024. In Goharian, N., Tonellotto, N., He, Y., Lipani, A., McDonald, G., Macdonald, C. and Ounis, I. (eds), Advances in Information Retrieval (pp. 60-66). Cham: Springer Nature Switzerland.
Alkhalifa, R., Borkakoty, H., Deveaud, R., El-Ebshihy, A., Espinosa-Anke, L., Fink, T., Galuščáková, P., Gonzalez-Saez, G., Goeuriot, L., Iommi, D., Liakata, M., Madabushi, H.T., Medina-Alias, P., Mulhem, P., Piroi, F., Popel, M. and Zubiaga, A., 2024. Overview of the CLEF 2024 LongEval Lab on Longitudinal Evaluation of Model Performance. In Goeuriot, L., Mulhem, P., Quénot, G., Schwab, D., Di Nunzio, G.M., Soulier, L., Galuščáková, P., García Seco de Herrera, A., Faggioli, G. and Ferro, N. (eds), Experimental IR Meets Multilinguality, Multimodality, and Interaction (pp. 208-230). Cham: Springer Nature Switzerland.
Alkhalifa, R., Borkakoty, H., Deveaud, R., El-Ebshihy, A., Espinosa-Anke, L., Fink, T., Galuščáková, P., Gonzalez-Saez, G., Goeuriot, L., Iommi, D., Liakata, M., Madabushi, H. T., Medina-Alias, P., Mulhem, P., Piroi, F., Popel, M., & Zubiaga, A. (2024). Extended overview of the CLEF 2024 LongEval Lab on Longitudinal Evaluation of Model Performance. CEUR Workshop Proceedings, 3740, 2267-2289. https://ceur-ws.org/Vol-3740/
Staudinger, M., El-Ebshihy, A., Ningtyas, A.M., Piroi, F. and Hanbury, A., 2024. AMATU@ SimpleText2024: Are LLMs any good for scientific leaderboard extraction. In Faggioli, G., Ferro, N., Galuščáková, P. and García Seco de Herrera, A. (eds), Working Notes of CLEF 2024 – Conference and Labs of the Evaluation Forum. CEUR Workshop Proceedings. Online: CEUR-WS.
Ningtyas, A.M., El-Ebshihy, A., Piroi, F. and Hanbury, A., 2024. Improving Laypeople Familiarity with Medical Terms by Informal Medical Entity Linking. In Goeuriot, L., Mulhem, P., Quénot, G., Schwab, D., Di Nunzio, G.M., Soulier, L., Galuščáková, P., García Seco de Herrera, A., Faggioli, G. and Ferro, N. (eds), Experimental IR Meets Multilinguality, Multimodality, and Interaction (pp. 113-126). Cham: Springer Nature Switzerland.
Kovacevic, F., El-Ebshihy, A., Piroi, F. and Rauber, A., n.d. Extending Content-based Scientific Knowledge Graphs with Research Results. KG-NeSy workshop in AIRoV 2024 – The First Austrian Symposium on AI, Robotics, and Vision
Adamakis, E., Boch, M., Bampoulidis, A., Margetis, G., Gindl, S., Stephanidis, C. (2023). Visualizing the risks of de-anonymization in high-dimensional data. 6th International Conference on Information Technology & Systems (ICITS’23).
Boch, M., Adamakis, E., Gindl, S., Margetis, G., Stephanidis, C. (2023). Anonymisation Methods for High-Dimensional and Complex Data based on Privacy Models for the Prevention of De-Anonymization Attacks. 11st World Conference on Information Systems and Technologies (WorldCIST’23).
Duh, D., Goschlberger, B., Boch, M., Graser, G., Gross, M., Pitzschke, A., & Sengschmid, E. (2023). Design and Development of a Social Micro-Learning Platform in the context of Tactile Learning Materials for Students with Visual Impairments. In The 15th International Conference on Education Technology and Computers (pp. 189-194).
Boch, M.; Gindl, S.; Barnett, A.; Margetis, G.; Mireles, V.; Adamakis, E. and Knoth, P. (2022). A Systematic Review of Data Management Platforms. In: WorldCIST’22, 12-14 Apr 2022, Budva, Montenegro.
Ghafourian, Y. (2022). Relevance Models Based on the Knowledge Gap. In Advances in Information Retrieval: 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II (pp. 488-495).
Taha, A. A., Papariello, L., Bampoulidis, A., Knoth, P., and Lupu, M. (2020). Formal analysis and estimation of chance in datasets based on their properties. IEEE Transactions on Knowledge and Data Engineering,xx(x):xx–xx.
Helminger, L., Kales, D., Rechberger, C., Walch, R., Bampoulidis, A., and Bruni, A. Privately Connecting Mobility to Infectious Diseases via Applied Cryptography. In IEEE Symposium on Security and Privacy
Lode, A. U. J., Alon, O. E., Bastarrachea-Magnani, M. A., Bhowmik, A., Buchleitner, A., Cederbaum, L. S., Chitra, R., Fasshauer, E., de Forges de Parny, L., Haldar, S. K., Leveque, C., Lin, R., Madsen, L. B., Molignini, P., Papariello, L., Schäfer, F., Strelstov, A. I., Tsatsos, M. C., and S. E. Weiner (2020). MCTDH-X: The multiconfigurational time-dependent Hartree method for indistinguishable particles high-performance computation project. In High Performance Computing in Science and Engineering. Springer, Cham.
Livne, M., Rieger, J., Aydin, O. U., Taha, A. A., Akay, E. M., Kossen, T., … & Madai, V. I. (2019). A U-Net deep learning framework for high performance vessel segmentation in patients
with cerebrovascular disease. Frontiers in neuroscience, 13, 97.
Lupu, M. (2019). Keeping on the good path.
Lupu, M., & List, J. (2018). Conferences 2017. World Patent Information, 52, 68-71.