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Dr. S.S. (Sahand) Mohammadi Ziabari PhD

Faculteit der Natuurwetenschappen, Wiskunde en Informatica
Graduate School of Informatics
Bezoekadres
  • Science Park 904
Postadres
  • Postbus 94214
    1090 GE Amsterdam
Contactgegevens
  • Publicaties

    2026

    • Ahmadian, M., Bodalal, Z., Adib, M., Mohammadi Ziabari, S. S., Bos, P., Martens, R. M., Agrotis, G., Vens, C., Karssemakers, L., Al-Mamgani, A., de Graaf, P., Jasperse, B., Brakenhoff, R. H., Leemans, C. R., Beets-Tan, R. G. H., van den Brekel, M. W. M., & Castelijns, J. A. (2026). Explainable feature selection combining particle swarm optimisation with adaptive LASSO for MRI radiogenomics: Predicting HPV status in oropharyngeal cancer. Computer Methods and Programs in Biomedicine, 275, Article 109204. https://doi.org/10.1016/j.cmpb.2025.109204
    • Bakker, S., Ma, Y., & Mohammadi Ziabari, S. S. (2026). Addressing Label Scarcity: Hybrid Anomaly Detection in Mental Healthcare Billing. In E. Pardede, Q. Ma, G. Kotsis, T. Amagasa, A. Nadamoto, & I. Kahlil (Eds.), Information Integration and Web Intelligence: 27th International Conference, iiWAS 2025, Matsue, Japan, December 8–10, 2025 : proceedings (pp. 112–126). (Lecture Notes in Computer Science; Vol. 16330). Springer. https://doi.org/10.1007/978-3-032-11976-6_8 [details]
    • Braakman, N. M., Mohammadi Ziabari, S. S., Alsahag, A. M. M., & Nasser Al Husaini, Y. (2026). Intrinsic interpretability at parity: Attention-Based RL–MIL for student outcome prediction. Natural Language Processing Journal, 14, Article 100204. https://doi.org/10.1016/j.nlp.2026.100204 [details]
    • Brakenhoff , B., Alsahag, A. M. M., & Mohammadi Ziabari, S. S. (2026). Dynamic GNNs for Predicting Train Cancellations on the Dutch Railway Network: A Multi-Season Study of Environmental and Operational Factors. Digital Technologies Research and Applications, 5(1), 32-52. https://doi.org/10.54963/dtra.v5i1.1709 [details]
    • Leneman, T., Alsahag, A. M. M., & Mohammadi Ziabari, S. S. (2026). Explainable AI for subseasonal forecasting of the north atlantic oscillation. Machine Learning for Computational Science and Engineering, 2(1), Article 6. https://doi.org/10.1007/s44379-026-00055-1 [details]
    • Lin, B. Y., Mohammadi Ziabari, S. S., Nasser Al Husaini, Y., & Alsahag, A. M. M. (2026). SG-MuRCL: Smoothed Graph-Enhanced Multi-Instance Contrastive Learning for Robust Whole-Slide Image Classification. Information (Switzerland), 17(1), Article 37. https://doi.org/10.3390/info17010037 [details]
    • van Beveren, I., Sergidou, E., & Mohammadi Ziabari, S. (2026). Evaluating Deep Learning-Based Speaker Verification Systems: A Comparative Study Across Open-Source and Forensic Datasets. In A. Panchenko, D. Gubanov, M. Khachay, A. Kuznetsov, N. Loukachevitch, A. Kuznetsov, I. Nikishina, M. Panov, P. M. Pardalos, A. V. Savchenko, E. Tsymbalov, E. Tutubalina, A. Kasieva, & D. I. Ignatov (Eds.), Analysis of Images, Social Networks and Texts: 12th International Conference, AIST 2024, Bishkek, Kyrgyzstan, October 17–19, 2024 : revised selected papers (pp. 153-163). (Communications in Computer and Information Science; Vol. 2364). Springer. https://doi.org/10.1007/978-3-031-97019-1_12 [details]

    2025

    • Anwar, K., & Mohammadi Ziabari, S. S. (2025). Attention to the Branches: A Comparative Analysis of FairMOT with Transformers on Fish Dataset. In C. Sombattheera, P. Weng, & J. Pang (Eds.), Multi-disciplinary Trends in Artificial Intelligence: 17th International Conference, MIWAI 2024, Pattaya, Thailand, November 11–15, 2024 : proceedings (Vol. I, pp. 64–76). (Lecture Notes in Computer Science; Vol. 15431), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-981-96-0692-4_6 [details]
    • Ashtar, D., Mohammadi Ziabari, S., & Alsahag, A. M. M. (2025). Hybrid Forecasting for Sustainable Electricity Demand in The Netherlands Using SARIMAX, SARIMAX-LSTM, and Sequence-to-Sequence Deep Learning Models. Sustainability, 17(16), Article 7192. https://doi.org/10.3390/su17167192 [details]
    • Braakman, J., Mohammadi Ziabari, S. S., & Korver, A. (2025). Enhancing Soil Pollution Prediction Through Expert-Defined Risk Zones and Machine Learning: A Case Study in the Netherlands. In P. Delir Haghighi, M. Greguš, G. Kotsis, & I. Khalil (Eds.), Information Integration and Web Intelligence: 26th International Conference, iiWAS 2024, Bratislava, Slovak Republic, December 2–4, 2024 : proceedings (Vol. II, pp. 219-225). (Lecture Notes in Computer Science; Vol. 15343). Springer. https://doi.org/10.1007/978-3-031-78093-6_19 [details]
    • Chen, J., Alsahag, A. M. M., & Mohammadi Ziabari, S. S. (2025). An analytics framework for interpretable subseasonal forecasting under decadal climate variability. Decision Analytics Journal, 17, Article 100660. https://doi.org/10.1016/j.dajour.2025.100660 [details]
    • Chen, X., Liu, H., & Mohammadi Ziabari, S. (2025). Efficient Sparse MLPs Through Motif-Level Optimization Under Resource Constraints. AI, 6(10), Article 266. https://doi.org/10.3390/ai6100266 [details]
    • Coolwijk, S., Mohammadi Ziabari, S. S., & Angileri, F. (2025). Vision Transformer Approach to Customer Churn Prediction Radar Chart Image Classification for Non-subscription Based E-commerce. In P. Delir Haghighi, M. Greguš, G. Kotsis, & I. Khalil (Eds.), Information Integration and Web Intelligence: 26th International Conference, iiWAS 2024, Bratislava, Slovak Republic, December 2–4, 2024 : proceedings (Vol. II, pp. 75–80). (Lecture Notes in Computer Science; Vol. 15343). Springer. https://doi.org/10.1007/978-3-031-78093-6_6 [details]
    • Curiël, R., Alsahag, A. M. M., & Mohammadi Ziabari, S. S. (2025). Integrating Climate and Economic Predictors in Hybrid Prophet–(Q)LSTM Models for Sustainable National Energy Demand Forecasting: Evidence from The Netherlands. Sustainability, 17(19), Article 8687. https://doi.org/10.3390/su17198687 [details]
    • Katona, Z., Mohammadi Ziabari, S. S., & Karimi Nejadasl, F. (2025). MARINE: A Computer Vision Model for Detecting Rare Predator-Prey Interactions in Animal Videos. In A. Dasgupta, R. U. Kiran, R. El Shawi, S. Srirama, & M. Adhikari (Eds.), Big Data and Artificial Intelligence: 12th International Conference, BDA 2024, Hyderabad, India, December 17–20, 2024 : proceedings (pp. 183–199). (Lecture Notes in Computer Science; Vol. 15526). Springer. https://doi.org/10.1007/978-3-031-81821-9_11 [details]
    • Tigchelaar, K., Mohammadi Ziabari, S. S., & Mulder, J. (2025). The Integration of Federated Learning Techniques in Predictive Aircraft Maintenance Using Cloud Services. In S. Wu, X. Su, X. Xu, & B. H. Kang (Eds.), Knowledge Management and Acquisition for Intelligent Systems: 20th Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2024, Kyoto, Japan, November 18–19, 2024 : proceedings (pp. 203-213). (Lecture Notes in Computer Science; Vol. 15372), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-981-96-0026-7_16 [details]
    • Van de Sype, L., Vert, M., Sharpanskykh, A., & Mohammadi Ziabari, S. S. (2025). Effects of Unplanned Incoming Flights on Airport Relief Processes After a Major Natural Disaster. Aerospace, 12(10), Article 857. https://doi.org/10.3390/aerospace12100857 [details]
    • Zhu, C., Mohammadi Ziabari, S. S., & Alsahag, A. M. M. (2025). Task-Adaptive Debiasing with SCM for Sentiment Analysis. Machine Learning for Computational Science and Engineering, 1(2), Article 41. https://doi.org/10.1007/s44379-025-00043-x [details]

    2024

    • de Bosscher, B. C. D., Mohammadi Ziabari, S. S., & Sharpanskykh, A. (2024). Towards a Better Understanding of Agent-Based Airport Terminal Operations Using Surrogate Modeling. In L. G. Nardin, & S. Mehryar (Eds.), Multi-Agent-Based Simulation XXIV: 24th International Workshop, MABS 2023, London, UK, May 29–June 2, 2023 : revised selected papers (pp. 16-29). (Lecture Notes in Computer Science; Vol. 14558). Springer. https://doi.org/10.1007/978-3-031-61034-9_2 [details]
    • van de Sande, S. N. P., Alsahag, A. M. M., & Mohammadi Ziabari, S. S. (2024). Enhancing the Predictability of Wintertime Energy Demand in The Netherlands Using Ensemble Model Prophet-LSTM. Processes, 12(11), Article 2519. https://doi.org/10.3390/pr12112519 [details]

    2023

    • Chikhi, A., Mohammadi Ziabari, S. S., & van Essen, J. W. (2023). A Comparative Study of Traditional, Ensemble and Neural Network-Based Natural Language Processing Algorithms. Journal of Risk and Financial Management, 16(7), Article 327. https://doi.org/10.3390/jrfm16070327 [details]
    • De Bosscher, B. C. D., Mohammadi Ziabari, S. S., & Sharpanskykh, A. (2023). A comprehensive study of agent-based airport terminal operations using surrogate modeling and simulation. Simulation Modelling Practice and Theory, 128, Article 102811. https://doi.org/10.1016/j.simpat.2023.102811 [details]
    • De Leeuw, B., Mohammadi Ziabari, S. S., & Sharpanskykh, A. (2023). Surrogate Modeling of Agent-Based Airport Terminal Operations. In F. Lorig, & E. Norling (Eds.), Multi-Agent-Based Simulation XXIII - 23rd International Workshop, MABS 2022, Revised Selected Papers (pp. 82-94). (Lecture Notes in Computer Science; Vol. 13743), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-031-22947-3_7
    • Deshamudre, R., Mohammadi Ziabari, S. S., & van Houten, M. (2023). Enhancing AI Adoption in Healthcare: A Data Strategy for Improved Heart Disease Prediction Accuracy Through Deep Learning Techniques. In P. Delir Haghighi, E. Pardede, G. Dobbie, V. Yogarajan, N. A. S. ER, G. Kotsis, & I. Khalil (Eds.), Information Integration and Web Intelligence: 25th International Conference, iiWAS 2023, Denpasar, Bali, Indonesia, December 4–6, 2023 : proceedings (pp. 13-19). (Lecture Notes in Computer Science; Vol. 14416). Springer. https://doi.org/10.1007/978-3-031-48316-5_2 [details]
    • Hooftman, D., Mohammadi Ziabari, S. S., & Snijder, J. (2023). Exploring CycleGAN for Bias Reduction in Gender Classification: Generative Modelling for Diversifying Data Augmentation. In H. Lu, M. Blumenstein, S.-B. Cho, C.-L. Liu, Y. Yagi, & T. Kamiya (Eds.), Pattern Recognition: 7th Asian Conference, ACPR 2023, Kitakyushu, Japan, November 5–8, 2023 : proceedings (Vol. III, pp. 26-40). (Lecture Notes in Computer Science; Vol. 14408). Springer. https://doi.org/10.1007/978-3-031-47665-5_3 [details]

    2022

    • Janssen, S., Sharpanskykh, A., & Mohammadi Ziabari, S. S. (2022). Using Causal Discovery to Design Agent-Based Models. In K. H. Van Dam, & N. Verstaevel (Eds.), Multi-Agent-Based Simulation XXII - 22nd International Workshop, MABS 2021, Revised Selected Papers (pp. 15-28). (Lecture Notes in Computer Science; Vol. 13128), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-94548-0_2

    2021

    • Mekić, A., Mohammadi Ziabari, S. S., & Sharpanskykh, A. (2021). Systemic agent-based modeling and analysis of passenger discretionary activities in airport terminals. Aerospace, 8(6), Article 162. https://doi.org/10.3390/aerospace8060162
    • Mohammadi Ziabari, S. S., Sanders, G., Mekic, A., & Sharpanskykh, A. (2021). Demo Paper: A Tool for Analyzing COVID-19-Related Measurements Using Agent-Based Support Simulator for Airport Terminal Operations. In F. Dignum, J. M. Corchado, & F. De La Prieta (Eds.), Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection - 19th International Conference, PAAMS 2021, Proceedings (pp. 359-362). (Lecture Notes in Computer Science; Vol. 12946), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-85739-4_32
    • Sanders, G., Mohammadi Ziabari, S. S., Mekić, A., & Sharpanskykh, A. (2021). Agent-Based Modelling and Simulation of Airport Terminal Operations Under COVID-19-Related Restrictions. In F. Dignum, J. M. Corchado, & F. De La Prieta (Eds.), Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection - 19th International Conference, PAAMS 2021, Proceedings (pp. 214-228). (Lecture Notes in Computer Science; Vol. 12946), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-85739-4_18

    2020

    • Mohammadi Ziabari, S. S., & Treur, J. (2020). A modeling environment for dynamic and adaptive network models implemented in matlab. In X.-S. Yang, S. Sherratt, N. Dey, & A. Joshi (Eds.), Fourth International Congress on Information and Communication Technology: ICICT 2019, London (Vol. 1, pp. 91-111). (Advances in Intelligent Systems and Computing; Vol. 1041). Springer. https://doi.org/10.1007/978-981-15-0637-6_8

    2018

    • Mohammadi Ziabari, S. S., & Treur, J. (2018). Computational Analysis of Gender Differences in Coping with Extreme Stressful Emotions. Procedia Computer Science, 145, 376-385. https://doi.org/10.1016/j.procs.2018.11.088
    This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list.
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