Wrona, P., Grzenda, M., Enabling Semi-Supervised Travel Mode Prediction Through Synthetic Unlabelled Trip Instances,
accepted for and presented at ECML-PKDD (SoGood workshop), 15-19 September 2025, Porto,
Portugal, to be published in Springer
joint post-conference workshop proceedings14
Grzenda, M., Luckner, M., Bella, C., Understanding Tour-Related Factors Influencing Travel Mode
Choices in Urban Areas,
accepted for and presented at ECML-PKDD 2024, 9-13 September 2024, Vilnius, Lithuania, to be published in Springer
ECML-PKDD workshop proceedings (SoGood workshop), author's version (submitted manuscript) available on request
14
Selected Publications
H. M. Gomes, J. Read, M. Grzenda, B. Pfahringer and A. Bifet, SLEADE: Disagreement-Based Semi-Supervised
Learning for Sparsely Labeled Evolving Data Streams, in IEEE Transactions on Knowledge and Data Engineering,
vol. 38, no. 3, pp. 1973-1985, March 2026, doi: 10.1109/TKDE.2025.3647050,
https://doir.org/10.1109/TKDE.2025.3647050, 202614
Wrona, P., Sienkiewicz, E., Grzenda, M., Probabilistic Spatial Modelling of Travel Mode Choices with Synthetic Instances. In: Rupino da Cunha, P., Themistocleous, M. (eds) Information Systems. EMCIS 2025. Lecture Notes in Business Information Processing, vol 572. Springer, Cham
https://doi.org/10.1007/978-3-032-18484-9_20, 2026
14
Mirgos, M., Grzenda, M., Towards Integrating Monotonicity Constraints Into Hoeffding Trees for Binary Classification. In: Martínez, L., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2025. IDEAL 2025. Lecture Notes in Computer Science, vol 16238. Springer, Cham.
https://doi.org/10.1007/978-3-032-10486-1_24, 2026
14
Hassani, A., Nicińska, A., Drabicki, A., Zawojska, E., Sousa Santos, G., Kula, G., Grythe, H.,
Zawieska, J., Jaczewska, J., Rachubik, J., Archanowicz-Kudelska, K., Zagórska, K., Grzenda,
M., Kubecka, M., Luckner, M., et al, Air quality and transport behaviour: sensors, field, and
survey data from Warsaw, Poland,
Scientific Data, vol. 11(1), Springer Nature,
https://doi.org/10.1038/s41597-024-04111-4, 2024
14
Luckner, M., Wrona, P., Grzenda, M., Łysak, A., Analysing Urban Transport Using Synthetic Journeys. In: Franco, L., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science - ICCS 2024. ICCS 2024. Lecture Notes in Computer Science, vol 14838. Springer, Cham,
https://doi.org/10.1007/978-3-031-63783-4_10,
2024
14
Golik, P., Grzenda, M., Sienkiewicz, E., Hybrid Ensemble-Based Travel Mode Prediction, in: Miliou, I., Piatkowski, N., Papapetrou, P. (eds) Advances in Intelligent Data Analysis XXII. IDA 2024. Lecture Notes in Computer Science, vol 14641. Springer, Cham,
https://doi.org/10.1007/978-3-031-58547-0_16
2024
2
Grzenda, M., Luckner, M., Brzozowski, Ł., Quantifying Parking Difficulty with Transport and Prediction Models for Travel Mode Choice Modelling. In: Mikyska, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds), Computational Science - ICCS 2023. International Conference on Computational Science, Prague, Czechia, 2023. Lecture Notes in Computer Science, vol 10477. Springer, Cham,
pdf,
https://doi.org/10.1007/978-3-031-36030-5_40,
2023
1
Grzenda, M., Luckner, M., Wrona, P., Urban Traveller Preference Miner: Modelling Transport Choices with Survey Data Streams in: Amini, MR., Canu, S., Fischer, A., Guns, T., Kralj Novak, P., Tsoumakas, G. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2022. Grenoble, France. Lecture Notes in Computer Science, vol 13718. Springer, Cham,
https://doi.org/10.1007/978-3-031-26422-1_50
2023
1
Wrona, P., Grzenda, M., Luckner, M., Streaming Detection of Significant Delay Changes in Public Transport Systems. in: Groen, D., de Mulatier, C., Paszynski,
M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science.
International Conference on Computational Science, London, 2022. Lecture Notes in Computer Science,
vol 13353. Springer, Cham,
https://doi.org/10.1007/978-3-031-08760-8_41,
2022
1
Murilo Gomes, H., Grzenda, M., Mello, r., Read, J., Le Nguyen, M. H. , Bifet, A.,
A Survey on Semi-Supervised Learning for Delayed Partially Labelled Data Streams,
ACM Computing Surveys, 55, 4, ACM,
https://doi.org/10.1145/3523055,
2022, pp. 75:1-75:42
1
Grzenda, M., Quantifying Changes in Predictions of Classification Models for Data Streams.
in: Bouadi, T., Fromont, E., Hüllermeier, E. (eds) Advances in Intelligent Data Analysis XX.
IDA 2022. Lecture Notes in Computer Science, vol 13205. Springer, Cham,
https://doi.org/10.1007/978-3-031-01333-1_10,
2022, pp. 115-127
1
Grzenda, M., Legierski, J., Towards Increased Understanding of Open Data Use for Software Development,
Information Systems Frontiers, vol. 23(2), Springer,
https://doi.org/10.1007/s10796-019-09954-6,
2021, pp. 495-513
1
Kourtellis, N., Herodotou, H., Grzenda, M., Wawrzyniak, P., Bifet, A.,
S2CE: a hybrid cloud and edge orchestrator for mining exascale distributed streams,
Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems, ACM,
https://doi.org/10.1145/3465480.3466926,
2021, pp. 103-113
1
Kunicki, R., Grzenda, M., Towards Increasing Open Data Adoption Through Stream Data Integration and Imputation,
IEA/AIE 2021: Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices,
LNCS, vol. 12798, Springer, Cham,
https://doi.org/10.1007/978-3-030-79457-6_2,
2021, pp. 15-27
1
Grzenda, M., Gomes, H. M., Bifet, A., Delayed Labelling Evaluation for Data Streams,
Data Mining and Knowledge Discovery, DOI: 10.1007/s10618-019-00654-y, 34,
https://doi.org/10.1007/s10618-019-00654-y,
2020, pp. 1237-1266
14
Luckner, M., Grzenda, M., Kunicki, R., Legierski, J.,
IoT Architecture for Urban Data-Centric Services and Applications, ACM Transactions on Internet Technology,
https://doi.org/10.1145/3396850
2020, vol. 20, no. 3
14
Grzenda, M., Gomes, H. M., Bifet, A.,
Performance measures for evolving predictions under delayed labelling classification,
2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, United Kingdom,
10.1109/IJCNN48605.2020.9207256
2020, pp. 1-8
14
Grzenda, M., Analysing the Performance of Fingerprinting-Based Indoor Positioning:
The Non-trivial Case of Testing Data Selection, in Advances and Trends in Artificial Intelligence.
From Theory to Practice, LNAI, 11606, (Eds.) Wotawa, F. et al., Springer International Publishing,
https://doi.org/10.1007/978-3-030-22999-3_40,
2019, pp. 457-469
14
Grzenda, M., Kwasiborska, K., Zaremba, T., Hybrid Short Term Prediction to Address Limited Timeliness
of Public Transport Data Streams, Neurocomputing, Elsevier, Vol. 391,
https://doi.org/10.1016/j.neucom.2019.08.100,
2020, pp. 305-317
14
Grzenda, M., Ismail Awad, A., Furtak, J., Legierski, J. (Eds.),
Advances in Network Systems : Architectures,
Security, and Applications, Springer International Publishing,
https://doi.org/10.1007/978-3-319-44354-6
2017
14
Liebig, T., Peter, S. , Grzenda, M., Junosza-Szaniawski, K., Dynamic Transfer Patterns for
Fast Multi-modal Route Planning, in: Societal Geo-innovation: Selected papers of the 20th
AGILE conference on Geographic Information Science, Springer International Publishing,
https://doi.org/10.1007/978-3-319-56759-4_13,
2017, pp. 223-236
14
Grzenda, M., Kwasiborska, K., Zaremba, T., Combining Stream Mining and Neural Networks for
Short Term Delay Prediction, in Proceedings of International Joint Conference SOCO'17-CISIS'17-ICEUTE'17 Leon,
Spain, September 6-8, 2017, ed. : Perez G. et al, Springer International Publishing,
https://doi.org/10.1007/978-3-319-67180-2_18,
2018, pp. 188-197
14