Research Interests

• Statistical modelling of sequential observations, particularly in continuous time


• Method development for doubly stochastic processes, especially latent Markov models


• Application-driven data analysis, particularly in ecology as well as sports, psychology, sociology, medicine, health economics, and educational research

Publications in peer-reviewed journals

1. Coculla, A., Feldmann, C.C., Ogueta, M., Mews, S., Langrock, R., Stanewsky, R. (2026).
   Hsp90 buffers behavioral variability by regulating Pdf transcription in clock neurons of Drosophila melanogaster.
   PLOS Genetics, 22(2), e1012044.


2. Koslik, J.-O., Feldmann, C.C., Mews, S., Michels, R., Langrock, R. (2025).
   Inference on the state process of periodically inhomogeneous hidden Markov models for animal behaviour.
   The Annals of Applied Statistics, 19(4), 2724-2737.


3. Mews, S., Koslik, J.-O., Langrock, R. (2025).
   How to build your latent Markov model: The role of time and space.
   Statistical Modelling, 25(6), 481-507.


4. Bauhus, M.B., Mews, S., Kurtz, J., Brinker, A., Peuß, R., Anaya-Rojas, J.M. (2024).
   Tapeworm infection affects sleep-like behavior in three-spined sticklebacks.
   Scientific Reports, 14, 23395.


5. Mews, S., Langrock, R., Ötting, M., Yaqine, H., Reinecke, J. (2024).
   Maximum approximate likelihood estimation of general continuous-time state-space models.
   Statistical Modelling, 24(1), 9-28.


6. Trotter, A.W., Rathjens, L., Schmiegel, S., Mews, S., Cowley, P.D., Gennari, E. (2024).
   Short-term effects of standard procedures associated with surgical transmitter implantation on a benthic shark species requiring anaesthesia.
   Fisheries Research, 270, 106880.


7. Feldmann, C.C., Mews, S., Coculla, A. Stanewsky, R., Langrock, R. (2023).
   Flexible modelling of diel and other periodic variation in hidden Markov models.
   Journal of Statistical Theory and Practice, 17(3), 45.


8. Mews, S., Ötting, M. (2023).
   Continuous-time state-space modelling of the hot hand in basketball.
   AStA Advances in Statistical Analysis, 107, 313-326.


9. Mews, S., Surmann, B., Hasemann, L., Elkenkamp, S. (2023).
   Markov-modulated marked Poisson processes for modelling disease dynamics based on medical claims data.
   Statistics in Medicine, 42(21), 3804-3815.


10. Mews, S., Langrock, R., King, R., Quick, N. (2022).
    Multi-state capture-recapture models for irregularly sampled data.
    The Annals of Applied Statistics, 16(2), 982-998.


11. Schwarz, J.F.L., DeRango, E.J., Zenth, F., Kalberer, S., Hoffman, J.I., Mews, S., ..., Krüger, O. (2022).
    A stable foraging polymorphism buffers Galápagos sea lions against environmental change.
    Current Biology, 32(7), 1623-1628.e3.


12. Nagel, R., Mews, S., Adam, T., Stainfield, C., Fox-Clarke, C., Toscani, C., Langrock, R., Forcada, J., Hoffman, J. (2021).
    Movement patterns and activity levels are shaped by the neonatal environment in Antarctic fur seal pups.
    Scientific Reports, 11, 14323.


13. Schwarz, J.F.L., Mews, S., DeRango, E.J., Langrock, R., Piedrahita, P., Páez-Rosas, D., Krüger, O. (2021).
    Individuality counts: A new comprehensive approach to foraging strategies of a tropical marine predator.
    Oecologia, 195, 313-325.


14. Williams, R., Ashe, E., Yruretagoyena, Mastick, N., Siple, M., Wood, J., Joy, R., Langrock, R., Mews, S., Finne, E. (2021).
    Reducing vessel noise increases foraging in endangered killer whales.
    Marine Pollution Bulletin, 173, Part A, 112976.


15. van Beest, F., Mews, S., Elkenkamp, S., Schuhmann, P., Tsolak, D., Wobbe, T., ..., Langrock, R. (2019).
    Classifying grey seal behaviour in relation to environmental variability and commercial fishing activity – a multivariate hidden Markov model.
    Scientific Reports, 9, 5642.


16. Mews, S., Pöge, A. (2019).
    Das Zusammenspiel von Selbstbildern, motivationalen und emotionalen Orientierungen sowie deren Einfluss auf die Mathematikleistung in der PISA-Studie 2012.
    Zeitschrift für Erziehungswissenschaft, 22(4), 899-924.


17. Langrock, R., Adam, T., Leos-Barajas, V., Mews, S., Miller, D.L., Papastamatiou, Y.P. (2018).
    Spline-based nonparametric inference in general state-switching models.
    Statistica Neerlandica, 72(3), 179-200.​

Talks & posters

1. Modelling momentum in tennis: A latent-state approach to point outcomes and rally lengths. 16th Workshop on Stochastic Models, Statistics and Their Applications, Würzburg, March 2026.


2. Latent Markov models in ecology, MaSeMo: Markov. Semi-Markov Models and Associated Fields (from Theory to Application and back), Paris, France, July 2025.


3. Modelling disease dynamics based on claims data using Markov-modulated marked Poisson processes. Statistische Woche 2023, Dortmund, September 2023.


4. Modelling medical claims data using Markov-modulated market Poisson processes. 37th International Workshop on Statistical Modelling, Dortmund, July 2023.


5. Modelling longitudinal claims data using Markov-modulated marked Poisson processes. 15th CMStatistics, London, UK, December 2022.



6. Modelling claims data using Markov-modulated marked Poisson processes. 11th Young Researchers Workshop of the Centre for Statistics, Bielefeld, November 2022.


7. Uncovering behavioural niche mechanisms from individual-level ecological time series. CRC 212 Retreat, Hoherodskopf, August 2022.


8. Workshop: Hidden Markov models for animal movement and other ecological data. 8th International Statistical Ecology Conference, Cape Town, South Africa, June 2022.


9. Continuous-time latent-state modelling of delinquent behaviour in adolescence and young adulthood. 6th DAGStat, Hamburg, March 2022.


10. Continuous-time modelling of disease progression using claims data: how hard can it be?. 10th Young Researchers Workshop of the Centre for Statistics, Bielefeld, March 2022.


11. Continuous-time latent-state modelling of irregularly sampled sequential data. University of St Andrews Statistics Seminars, St Andrews, January 2022.


12. Latent-state modelling of delinquent behaviour in adolescence and young adulthood. Research Class on Quantitative Methods and Statistics, Bielefeld, November 2021.


13. Latent-state modelling of irregularly sampled sequential data. University of Edinburgh Statistics Seminars, Edinburgh, September 2021.


14. Uncovering behavioural niche mechanisms from individual-level ecological time series. CRC 212 Retreat, Helgoland, September 2021.


15. Continuous-time modelling of the hot hand effect in basketball free throws. 35th International Workshop on Statistical Modelling (held online), July 2021.


16. Latent-state modelling of patients’ disease progression in continuous time based on medical claims data. 9th Young Researchers Workshop of the Centre for Statistics, Bielefeld, July 2021.


17. Inference on individual variation in foraging strategies of Gálapagos sea lions. Virtual National Centre for Statistical Ecology meeting (held online), June 2021.


18. Continuous-time state-space modelling of delinquent behaviour in adolescence and young adulthood. Research Synthesis & Big Data (held online), Frankfurt am Main, May 2021.


19. Continuous-time state-space modelling of delinquent behaviour in adolescence and young adulthood. Statistics Seminar Series (held online), Bielefeld, January 2021.


20. Multi-state capture-recapture in continuous time. 7th International Statistical Ecology Conference (held online), June 2020.


21. Investigating the hot hand effect in continuous time. 8th Young Researchers Workshop of the Centre for Statistics, Bielefeld, November 2019.


22. A continuous-time Arnason-Schwarz model for the annual movement of bottlenose dolphins. Royal Statistical Society International Conference, Belfast, UK, September 2019.


23. A continuous-time capture-recapture model for annual movements of bottlenose dolphins. 34th International Workshop on Statistical Modelling, Guimarães, Portugal, July 2019.


24. A continuous-time capture-recapture model for the annual movement of bottlenose dolphins. Statistical Computing, Günzburg, July 2019.


25. A multi-state capture-recapture model in continuous time for the annual movement of bottlenose dolphins. 7th Young Researchers Workshop of the Centre for Statistics, Bielefeld, May 2019.


26. A continuous-time multi-state capture-recapture model for the annual movement of bottlenose dolphins on the east coast of Scotland. 5th DAGStat, Munich, March 2019.


27. Nonparametric estimation in hidden Markov models using the EM algorithm. 11th CMStatistics, Pisa, Italy, December 2018.


28. Nonparametric estimation in hidden Markov models using the EM algorithm. 6th Young Researchers Workshop of the Centre for Statistics, Bielefeld, December 2018.


29. Grey seal behaviour in relation to environmental variability and commercial fishing activity – an analysis using multivariate hidden Markov models. 6th International Statistical Ecology Conference, St Andrews, UK, July 2018.


30. Grey seal behaviour in relation to environmental variability and commercial fishing activity – an analysis using multivariate hidden Markov models. 5th Young Researchers Workshop of the Centre for Statistics, Bielefeld, June 2018.


31. Statistical Literacy von Schülerinnen und Schülern in Deutschland – Empirische Analysen auf der Grundlage von PISA 2012. Herbsttagung der Kommission Bildungsplanung, Bildungsorganisation und Bildungsrecht (KBBB) in der Deutschen Gesellschaft für Erziehungswissenschaft (DGfE), Paderborn, September 2016.