masha.medvedeva.bos@gmail.com

masha-medvedeva

ABOUT ME

I'm an Assistant Professor in Legal Technologies at Leiden University, working at the intersection of AI, law, and society. With a technical background and eight years in the legal domain, I focus on how algorithmic systems are developed, deployed, and evaluated in high-stakes contexts.

I specialize in machine learning, responsible AI, risk assessment, and the ethics of automation. I collaborate with courts, researchers, and policymakers to ensure these technologies align with societal values. I'm always open to applying this perspective to real-world challenges across research, policy, or industry.     View CV

PUBLICATIONS

2023
Medvedeva, M., McBride, P. (2023). Legal Judgment Prediction: If You Are Going to Do It, Do It Right. In Proceedings of the Workshops on Natural Legal Language Processing at EMNLP 2023
Schepers, I., Medvedeva, M., Bruijn, M., Wieling, M., & Vols, M. (2023). Predicting citations in Dutch case law with natural language processing. Artificial Intelligence and Law, 1-31.
Medvedeva, M., Wieling, M., & Vols, M. (2023). Rethinking the Field of Automatic Prediction of Court Decisions. Artificial Intelligence and Law, 31, 195-212
Rebernik, T., Tienkamp, T., Polsterer, K., Hukker, V., Medvedeva, M., van der Ploeg, M., Schepers, I., Sekeres, H.G., de Vries, W., Abur, D. and Jonkers, R., Noiray, A., Wieling, M. (2023). 5-minute formant adaptation task in Dutch children. In Proceedings of the 20th International Congress of Phonetic Sciences (ICPhS 2023).
2022
Diver, L., McBride, P., Medvedeva, M, Banerjee, A., D’hondt, E., Duarte Nicolau, T., Dushi, D., Gori, G., Van Den Hoven, E., Meessen, P., and Hildebrandt, M. (2022). Typology of legal technologies. In Cross-disciplinary Research in Computational Law (CRCL): Computational ’Law’ on Edge 2022
Medvedeva, M. (2022). Identification, Categorisation and Forecasting of Court Decisions. PhD thesis, University of Groningen
2021
Medvedeva, M., Dam, T., Wieling, M., Vols, M. (2021). Automatically Identifying Eviction Cases and Outcomes Within Case Law of Dutch Courts of First Instance. In Legal Knowledge and Information Systems (pp. 13-22). IOS Press.
Medvedeva, M., Üstun, A., Xu, X., Vols, M., Wieling, M. (2021). Automatic Judgement Forecasting for Pending Applications of the European Court of Human Rights. In Proceedings of the Workshops on Automated Semantic Analysis of Information in Legal Text (ASAIL 2021)
2020
Medvedeva, M., Xu, X., Wieling, M., & Vols, M. JURI SAYS: An Automatic Judgement Prediction System for the European Court of Human Rights. In Proceedings of JURIX 2020, pages 277 - 280.
Wieling, M., Tiede, M., Rebernik, T., de Jong, L., Braggaar, A., Bartelds, M., Medvedeva, M., Heisterkamp, P., Freire Offrede, T., Sekeres, H., Pot, A., van der Ploeg, M., Volkers, K. & Mills, G. (2020) A novel paradigm to investigate phonetic convergence in interaction. In Proceedings of 12th International Seminar on Speech Production.
Medvedeva, M., Wieling, M., & Vols, M. (2020). The Danger of Reverse-Engineering of Automated Judicial Decision-Making Systems. arXiv preprint arXiv:2012.10301.
Medvedeva, M., Vols, M., & Wieling, M. (2020). Using machine learning to predict decisions of the European Court of Human Rights. Artificial Intelligence and Law, 28(2), 237-266.
The publication is a required reading in multiple masters courses across Europe.
2019
Haagsma, H., Kreutz, T., Medvedeva, M., Walter, D., and Nissim, M. (2019). Overview of the Cross-Genre Gender Prediction Shared Task on Dutch at CLIN29. In Proceedings of the Shared Task on Cross-Genre Gender Prediction in Dutch at CLIN29 (GxG-CLIN29)
Wieling, M., Blankevoort, C., Hukker, V., Jacobi, J., de Jong, L., Keulen, S., Medvedeva, M., van der Ploeg, M., Pot, A., Rebernik, T., Veenstra, P., and Noiray, A. (2019). The Influence of Alcohol on L1 vs. L2 Pronunciation. In Proceedings of ICPhS 2019.
2018
Medvedeva, M., Vols, M., and Wieling, M. (2018). Judicial Decisions of the European Court of Human Rights: Looking into the Crystall Ball. In Proceedings of the Conference on Empirical Legal Studies in Europe 2018.
Basile, A., Dwyer, G., Medvedeva, M., Rawee, J., Haagsma, H., and Nissim, M. (2018). Simply the Best: Minimalist System Trumps Complex Models in Author Profiling. In International Conference of the Cross-Language Evaluation Forum for European Lan- guages, pages 143–156. Springer.
Kroon, M., Medvedeva, M., and Plank, B. (2018). When Simple N-gram Models Outperform Syntactic Approaches: Discriminating between Dutch and Flemish. In Proceedings of the Fifth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2018), pages 244–253.
2017
Basile, A., Dwyer, G., Medvedeva, M., Rawee, J., Haagsma, H., and Nissim, M. (2017a). Is There Life beyond N-grams? A Simple SVM-based Author Profiling System. In Working Notes of CLEF 2017-Conference and Labs of the Evaluation Forum. PAN Shared Task Winner.
Medvedeva, M., Haagsma, H., and Nissim, M. (2017). An Analysis of Cross-Genre and In-Genre Performance for Author Profiling in Social Media. In International Conference of the Cross-Language Evaluation Forum for European Languages, pages 211–223. Springer. Best Paper Award at CLEF 2017.
Basile, A., Dwyer, G., Medvedeva, M., Rawee, J., Haagsma, H., and Nissim, M. (2017b). N-gram: New Groningen Author-Profiling Model. In International Conference of the Cross-Language Evaluation Forum for European Languages, CEUR.
Medvedeva, M., Kroon, M., and Plank, B. (2017). When Sparse Traditional Models Out- perform Dense Neural Networks: the Curious Case of Discriminating between Similar Languages. In Proceedings of the Fourth Workshop on NLP for Similar Languages, Varieties and Dialects, pages 156–163. Association for Computational Linguistics.
2016
Busger op Vollenbroek, M., Carlotto, T., Kreutz, T., Medvedeva, M., Pool, C., Bjerva, J., Haagsma, H., and Nissim, M. (2016). GronUP: Groningen User Profiling: Notebook for PAN at CLEF 2016. In Balog, K., Cappellato, L., Ferro, N., and Macdonald, C., editors, Working Notes of CLEF 2016, CEUR, pages 846–857. Workshop Proceedings. PAN Shared Task Winner
Arkhangelshiy, T. and Medvedeva, M. (2016). Developing Morphologically Annotated Corpora for Minority Languages of Russia. In Proceedings of Corpus Linguistics Fest 2016, CEUR, pages 1–6