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Data Science Centre Data Science Centre

Outputs

Data Science Centre

Our members have produced a range of scientific outputs such as journal publications, conference papers, posters, and media interviews.
Academic publications
  • 2025

    • Dijkman, J., Dijkstra, M., van Roij, R., Welling, M., van de Meent, J., & Ensing, B. (2025). Learning Neural Free-Energy Functionals with Pair-Correlation Matching. Physical Review Letters, 134. doi: https://doi.org/10.1103/PhysRevLett.134.056103

    • Karabulut, E., Groth, P., & Degeler, V. 3K: Knowledge-Enriched Digital Twin Framework. IoT '24: Proceedings of the 14th International Conference on the Internet of Things, 188-193. doi: https://doi.org/10.1145/3703790.3703834

  • 2024
    • Angelakis, A. (2024). WED-347 Diagnosis of advanced liver fibrosis: the synergy of open data, synthetic data generation, CatBoost, and feature engineering. Journal of Hepatology, 80. doi: https://doi.org/10.1016/S0168-8278(24)01662-3
    • Angelakis, A. & Rass, A. (2024). A data-centric approach to class-specific bias in image data augmentation. arXiv. doi: https://doi.org/10.48550/arXiv.2403.04120
    • Bella, G., Helm, P., Koch, G. & Giunchiglia, F. (2024). Tackling Language Modelling Bias in Support of Linguistic Diversity. In The 2024 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’24). doi: https://doi.org/10.1145/3630106.3658925 
    • Beukers, N. G. F. M., Loos, B. G., van der Heijden, G. J. M. G., Stamatelou, E., Angelakis, A., & Su, N. (2024). The Prevalence of Comorbidities in Individuals with Periodontitis in a Private Periodontal Referral Practice. Journal of Clinical Medicine, 13(23), 7410. doi: https://doi.org/10.3390/jcm13237410
    • Degeler, V., Hadadian, M., Karabulut, E., Lazovik, A., van het Loo, H., Tello, A., Truong, H. (2024). DiTEC: Digital Twin for Evolutionary Changes in Water Distribution Networks. Application Areas. ISoLA 2024. Lecture Notes in Computer Science, vol 15223. Springer. doi: https://doi.org/10.1007/978-3-031-75390-9_5
    • Delouee, M.L., Degeler, V., Amthor, P., & Koldehofe, B. (2024). APP-CEP: Adaptive Pattern-level Privacy Protection in Complex Event Processing Systems. In Proceedings of the 10th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP. p. 486-497. doi: https://doi.org/10.5220/0012358700003648
    • Delouee, M. L., Pernes, D.G., Degeler, V., & Koldehofe, B. (2024). Towards Federated LLM-Powered CEP Rule Generation and Refinement. In Proceedings of the 18th ACM International Conference on Distributed and Event-Based Systems (DEBS’24). Association for Computing Machinery, p. 185–186. doi: 10.1145/3629104.3672429. 
    • Dijkman, J., Dijkstra, M., van Roij, R., Welling, M., van de Meent, J. & Ensing, B. (2024). Learning Neural Free-Energy Functionals with Pair-Correlation Matching. Preprint. https://doi.org/10.48550/arXiv.2403.15007
    • Helm, P. (2024). How platform power undermines diversity-oriented innovation. Internet Policy Review, 13. doi: https://doi.org/10.14763/2024.2.1780
    • Helm, P., Bella, G., Koch, G., & Giunchiglia, F. (2024). Diversity and language technology: how language modeling bias causes epistemic injustice. Ethics and Information Technology, 26(8). doi: https://doi.org/10.1007/s10676-023-09742-6
    • Helm, P., Lipp, B., & Pujadas, R. (2024). Generating reality and silencing debate: Synthetic data as discursive device. Big Data & Society, 11(2). doi: https://doi.org/10.1177/20539517241249447
    • Helm, P. & Matzner, T. (2024). Co-addictive human–machine configurations: Relating critical design and algorithm studies to medical-psychiatric research on “problematic Internet use”. New Media & Society, 26. doi: https://doi.org/10.1177/14614448231165916 

    • de Jong, T. M. H., Stamatelou, E., Rosema, N. A. M., Jansen, I. D. C., Brandt, B. W., Angelakis, A., Loos, B. G., van der Velden, U., & Danser, M. M. (2024). Effect of Daily Vitamin C Supplementation with or Without Flavonoids on Periodontal, Microbial, and Systemic Conditions Before and After Periodontal Therapy: A Case Series from an RCT. Journal of Clinical Medicine, 13(24). https://doi.org/10.3390/jcm13247571

    • Karabulut, E., Pileggi, S. F., Groth, P., & Degeler, V. (2024). Ontologies in Digital Twins: A Systematic Literature Review. Future Generation Computer Systems, 153. doi: https://doi.org/10.1016/j.future.2023.12.013
    • Khalil, A. Delouee, M.L., Degeler, V., Meuser, T., Anta, A.F, & Koldehofe, B. (2024). Driving Towards Efficiency: Adaptive Resource-Aware Clustered Federated Learning in Vehicular Networks. 22nd Mediterranean Communication and Computer Networking Conference (MedComNet). p. 1-10. doi: 10.1109/MedComNet62012.2024.10578208; [pdf]

    • Koch, G., Bella, G., Helm, P., & Giunchiglia, F. (2024). Layers of Technology in Pluriversal Design. Decolonising AI Language Technology with the LiveLanguage Initiative. Journal for Co-Design, 20. doi: https://doi.org/10.48550/arXiv.2405.01783 

    • Krause, L., Santamaria, S. B., & Kalo, J.-C. (2024). Graph representations for machine translation in dialogue settings. Proceedings of the Ninth Conference on Machine Translation, p. 1038–1046. doi: https://doi.org/10.18653/v1/2024.wmt-1.106

    • Lipp, B., Helm, P., Karafillidis, A., & Pujadas, R. (2024). De-centring the interface. Towards the integrated study of interfacial relations. Information, Communication & Society, 0. doi: https://doi.org/10.1080/1369118X.2024.2413110 

    • Moutafi M.K., Bates K.M., Aung T.N., Milian R.G., Xirou V., Vathiotis I.A., Gavrielatou N., Angelakis A., Schalper K.A., Salichos L., Rimm D.L. (2024). High-throughput transcriptome profiling indicates ribosomal RNAs to be associated with resistance to immunotherapy in non-small cell lung cancer (NSCLC). Journal for ImmunoTherapy of Cancer 12(6). doi: https://doi.org/10.1136/jitc-2024-009039

    • Tello, A., Degeler, V., Lazovik, A. (2024). Too Good To Be True: accuracy overestimation in (re)current practices for Human Activity Recognition. IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), p. 511-517, doi: https://doi.org/10.1109/PerComWorkshops59983.2024.10503465
    • Tello, A., Truong, H., Lazovik, A., & Degeler, V. (2024). Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks. Engineering Proceedings, 69(1). doi: https://doi.org/10.3390/engproc2024069050
    • Truong, H., Tello, A., Lazovik, A., & Degeler, V. (2024). Graph Neural Networks for Pressure Estimation in Water Distribution Systems, Water Resources Research, 60. doi: https://doi.org/10.1029/2023WR036741

    • Zakis, D. R., Brandt, B. W., van der Waal, S. V., Keijser, B. J. F., Crielaard, W., van der Plas, D. W. K., … Zaura, E. (2024). The effect of different sweeteners on the oral microbiome: a randomized clinical exploratory pilot study. Journal of Oral Microbiology, 16(1): 2369350. https://doi.org/10.1080/20002297.2024.2369350

    • Vickers, P., Ludovica, A., Alfano, M.,... Helm, P., et al. (2024). Development of a Novel Methodology for Ascertaining Scientific Opinion and Extent of Agreement. PLOS ONE 19. doi: https://doi.org/10.1371/journal.pone.0313541

    • de Vito, G., Ferrucci, F., Angelakis, A. (2024). HELIOT: LLM-Based CDSS for Adverse Drug Reaction Management. arXiv. doi: https://doi.org/10.48550/arXiv.2409.16395

    • Yousefi, M.H.N., Degeler, V., & Lazovik, A. Self-Adaptive Service Selection for Machine Learning Continuous Delivery. 2024 IEEE International Conference on Web Services (ICWS), p. 1048-1056. doi: https://doi.org/10.1109/ICWS62655.2024.00123

  • 2023
    • Abegaz, F., Abedini, D., White, F., Guerrieri, A., Zancarini, A., Dong, L., Westerhuis, J. A., van Eeuwijk, F., Bouwmeester, H., & Smilde, A. K. (2023). A strategy for differential abundance analysis of sparse microbiome data with group-wise structured zeros. bioRxiv preprint. doi: https://doi.org/10.1101/2023.07.24.549296
    • Angelakis, A., Soulioti, I., & Filippakis, M. (2023). Diagnosis of acute myeloid leukaemia on microarray gene expression data using categorical gradient boosted trees. Heliyon, 9 (10). doi: https://doi.org/10.1016/j.heliyon.2023.e20530
    • Bella, G., Helm, P. Koch, G., & Giunchiglia, F. (2023). Towards Bridging the Digital Language Divide. arXiv preprint. doi: https://doi.org/10.48550/arXiv.2307.13405
    • Boelrijk, J., van Herwerden, D., Ensing, B., Forré, P., & Samanipour, S. (2023). Predicting RP-LC retention indices of structurally unknown chemicals from mass spectrometry data. Journal of Cheminformatics, 15 (28). doi: https://doi.org/10.1186/s13321-023-00699-8
    • Feraud, M., O'Brien, J. W., Samanipour, S., Dewapriya, P., van Herwerden, D., Kaserzon, S., Wood, I., Rauert, C., & Thomas, K. V. InSpectra – A platform for identifying emerging chemical threats (2023). Journal of Hazardous Materials, 455. doi:  https://doi.org/10.1016/j.jhazmat.2023.131486

    • Helm, P., De Götzen, A., Cernuzzi, L., Ruiz Correa, S., Diwakar, S., & Gatica-Perez, D (2023). Diversity and Neocolonialism in Big Data Research. Big Data & Society, 10(2). doi: https://doi.org/10.1177/20539517231206802

    • Helm, P. & Matzner, T. (2023). Co-addictive human–machine configurations: Relating design and algorithm studies to medical-psychiatric research on “problematic Internet use”. New Media & Society, https://doi.org/10.1177/1461444823116591

    • Guha, S., Khan, F. A., Stoyanovich, J., Schelter, S. (2023). Automated data cleaning can hurt fairness in machine learning-based decision making. 2023 IEEE 39th International Conference on Data Engineering. doi: https://doi.org/10.1109/ICDE55515.2023.00303
    • Liu, X., Karimi Nejadasl, F., van Gemert, J. C., Booij, O., & Pintea, S. L. (2023). Objects do not disappear: Video object detection by single-frame object location anticipation. Presented at the International Conference on Computer Vision. doi: https://doi.org/10.48550/arXiv.2308.04770
    • Lunansky, G., Hoekstra, R. H., & Blanken, T. (2023). Disentangling the role of affect in the evolution of depressive compalints using complex dynamical networks. Collabra:Psychology, 9 (1). doi: https://doi.org/10.1525/collabra.74841
    • Möller, M., Vermeer, S.A.M., & Baumgartner, S. (2023). Cutting through the comment chaos: A supervised machine learning approach to identifying relevant YouTube comments. Social Science Computer Review. doi: https://doi.org/10.1177/08944393231173895

    • Müller, N., Groen, I., & Scholte, S. (2023). Pre-training on high-quality natural image data reduces DCNN texture bias. 2023 Conference on Cognitive Comutational Neuroscience. doi: https://doi.org/10.32470/CCN.2023.1294-0

    • Rieder, B., Borra, E. K., Coromina, Ò., & Matamoros-Fernández, A. (2023). Making a living in the creator economy: A large-scale study of linking on YouTube. Social Media + Society, 9 (2). https://doi.org/10.1177/20563051231180628

    • van Spengler, M., Berkhout, E., & Mettes, P. (2023). Poincaré ResNet. Presented at International Conference on Computer Vision. doi: https://doi.org/10.48550/arXiv.2303.14027 
    • van Spengler, M., Wirth, P., & Mettes, P. (2023). HypLL: The Hyperbolic Learning Library. ACM MM 2023 Open-Source Software Competition. doi: https://doi.org/10.48550/arXiv.2306.06154 
    • Wei, W., Oswald, M. R., Karimi Nejadasl, F., & Gevers, T. (2023). APNet: Urban-level scene segmentation of aerial images and point clouds. Presented at the International Conference on Computer Vision. doi: https://doi.org/10.48550/arXiv.2309.17162
    • Haider, I., Yunmeng, Z., White, F., Li, C., Incitti, R., Alam, I., Gojobori, T., Ruyter-Spira, C., Al-Babili, S., & Bouwmeester, H. J. (2023). Transcriptome analysis of the phosphate starvation response sheds light on strigolactone biosynthesis in rice. The Plant Journal, 114. doi: https://doi.org/10.1111/tpj.16140
  • 2022

    • Baas, J., van Wissen, L., Reinders, J., Dastani, M., & Feelders, A. (2022). Adding Domain Knowledge to Improve Entity Resolution in 17th and 18th Century Amsterdam Archival Records. In Towards a Knowledge-Aware AI (pp. 90-104). IOS Press. https://doi.org/10.3233/SSW22001

    • Bracks, C., & Moss, F. C. (2022). Totoli’s art of lelegesan: Analyzing sociocultural context and musical content. OSF Preprints. https://doi.org/10.31219/osf.io/5tsxa

    • Burger, J., Isvoranu, A.M., Lunansky, G., Haslbeck, J., Epskamp, S., Hoekstra, R.H., Fried, E.I., Borsboom, D. and Blanken, T.F., (2022). Reporting standards for psychological network analyses in cross-sectional data. Psychological Methods. doi: https://doi.org/10.1037/met0000471

    • Harasim, D., Affatato, G., & Moss, F. C. (2022). midiVERTO: A Web Application to Visualize Tonality in Real Time. In M. Montiel, O. A. Agustín-Aquino, F. Gómez, J. Kastine, E. Lluis-Puebla, & B. Milam (Eds.), Mathematics and Computation in Music (pp. 363–368). Springer International Publishing. doi: https://doi.org/10.1007/978-3-031-07015-0_31

    • Kuiper, M.E., Chambon, M., de Bruijn, A.L., Reinders Folmer, C., Olthuis, E.H., Brownlee, M., Kooistra, E.B., Fine, A., van Harreveld, F., Lunansky, G. and van Rooij, B. (2022). A Network Approach to Compliance: A Complexity Science Understanding of How Rules Shape Behavior. Journal of Business Ethics, 1 - 26. doi: https://doi.org/10.1007/s10551-022-05128-8

    • Moss, F. C., Affatato, G., & Harasim, D. (2022). Phantom Curves: Scientific Discovery through Interactive Music Visualization. In L. Pugin (Ed.), DLfM '22: Proceedings of the 9th International Conference on Digital Libraries for Musicology, Association for Computing Machinery (pp.. https://doi.org/10.1145/3543882.3543886

    • Renai, L., Del Bubba, M., Samanipour, S., Stafford, R., & Gargano, A.F.G. (2022). Development of a comprehensive two-dimensional liquid chromatographic mass spectrometric method for the non-targeted identification of poly- and perfluoroalkyl substances in aqueous film-forming foams. Analytica Chimica Acta, 1232. doi: https://doi.org/10.1016/j.aca.2022.340485

    • Rieder, B., Peeters, S. C. J., & Borra, E. K. (2022). From tool to tool-making: Reflections on authorship in social media research software. Convergence : The International Journal of Research into New Media Technologies. https://doi.org/10.1177/13548565221127094

    • Samanipour, S., O'Brien, J., Reid, M., Thomas, K., & Praetorius, A. (2022). From molecular descriptors to intrinsic fish toxicity of chemicals: An alternative approach to chemical prioritization. Envrironmental Science & Technology. doi: https://doi.org/10.1021/acs.est.2c07353

    • Sano N., Lounifi I., Cueff G., Collet B., Clément G., Balzergue S., Huguet S., Valot B., Galland M., & Rajjou, L. (2022). Multi-Omics approaches unravel specific features of embryo and endosperm in rice seed germination. Frontiers in Plant Science, 13. doi:  https://doi.org/10.3389/fpls.2022.867263

    • Yang, F., van Herwerden, D., Preud’homme, H., & Samanipour, S. (2022). Collision Cross Section Prediction with Molecular Fingerprint Using Machine Learning. Molecules, 27(19), 6424. https://doi.org/10.3390/molecules27196424

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