CV

Click here for the PDF version of my CV.

Education

• PhD in Statistics, Bielefeld University, 2023-today
• MSc in Statistical Science, Bielefeld University, 2021-2023
• BSc in Economics (intermediate studies), Bielefeld University, 2020-2021
• BA in Business Administration, Bielefeld University of Applied Sciences, 2017-2020
  • Semester abroad, Budapest Business School, 2019/2020

Employment

• Research associate Statistics and Data Analysis Group, Bielefeld University, 2023-today
• Research assistant Statistics and Data Analysis Group, Bielefeld University, 2022-2023
• Working student Pricing Intelligence, CLAAS KGaA mbH, 2021-2022
• Intern Market Intelligence, CLAAS KGaA mbH, 2020
• Tutor in Mathematics and Statistics, Bielefeld University of Applied Sciences, 2018-2020

Publications

Peer-reviewed papers

• Michels, R., Koslik, J.-O. (2024)
  “On the combination of data smoothing and Markov-switching models”
  Journal of the Royal Statistical Society – Series C: Applied Statistics, qlad110.

Preprints

• Bachons, R., Koslik, J.-O., Michels, R., Ötting, M. (2024)
  “PEP: a tackle value measuring the prevention of expected points”
  arXiv preprint, arXiv:2407.08508
• Mews, S., Koslik, J.-O., Langrock, R. (2024)
  “How to build your latent Markov model - the role of time and space”
  arXiv preprint, arXiv:2406.19157
• Koslik, J.-O. (2024)
  “Hidden semi-Markov models with inhomogeneous state dwell-time distributions”
  arXiv preprint, arXiv:2405.13553
• Koslik, J.-O., Feldmann, C.C., Mews, S., Michels, R., Langrock, R. (2023)
  “Inference on the state process of periodically inhomogeneous hidden Markov models for animal behaviour”
  arXiv preprint, arXiv:2312.14583
• Dyck, J., Koslik, J.-O., Sauzet, O. (2023)
  “EgoCor: an R package to fit exponential semi-variograms to model the local spatial correlation structure of health outcomes”
  arXiv preprint, arXiv:2309.12979

Teaching

Workshops

Coorganised Workshop Hidden Markov Models for movement, acceleration and other ecological data – an introduction using moveHMM and momentuHMM in R
online, September 2024,
with Roland Langrock and Carlina Feldmann

Practical session for the Workshop Using hidden Markov models to uncover ecological state dynamics from biologging data
Tokyo Japan, March 2024

Tutorials and courses

Practical session on multivariate methods
Bachelor level, Bielefeld University, winter term 2024/2025

Practical session Mathematics for economists
Bachelor level, Bielefeld University, summer term 2024, winter term 2024/2025

Practical session on hidden Markov models
Master level, Bielefeld University, summer term 2024

• If you want to learn implementing HMMs and their extension (HSMMs, cont.-time HMMs, SSMs, MM(M)PPs) yourself, click here to check out the vignettes of the R package LaMa. They provide various illustrative examples for a wide range of latent Markov models.

Statistical Consulting
Master level, Bielefeld University, winter term 2023/2024, winter term 2024/2025

Practical session on generalised linear models (GLMs)
Master level, Bielefeld University, winter term 2023/2024

Grants and Awards

• German public-private scholarship, funding years 2019/2020 and 2022/2023
• Mobility grant of the Bielefeld Graduate School in Theoretical Sciences (BGTS)
  €4,000

Community involvement

Reviewer

• Journal of Computational and Graphical Statistics
• Journal of the Royal Statistical Society Series C
• Computational Statistics and Data Analysis
• Methods in Ecology and Evolution
• Movement Ecology

Other skills

• Programming: R (including Rcpp), C++, Python
• Tools: LaTeX, git, SQL
• Languages: German, English

Volunteering

• Member of the student council (Data Science & Statistical Science), Bielefeld University, 2021-2023
• Representing the interests of student assistants (SHK-Rat), Bielefeld University, 2022
• Voluntary service, AWO nursery school Werther, 2016-2017

Talks and Presentations

Talks

Efficient smoothness selection for nonparametric Markov-switching models via quasi restricted maximum likelihood
24. September 2024, Statistics Seminar, Göttingen, Germany

Exploring hidden dynamics: statistical inference in periodically inhomogeneous hidden Markov models for animal behaviour
4. September 2024, Royal Statistical Society Conference, Brighton, UK

Inference on the state process of periodically inhomogeneous hidden Markov models for animal behaviour
17. July 2024, International Statistical Ecology Conference, Swansea, Wales

Inference on the state process of periodically inhomogeneous hidden Markov models
16. February 2024, Young Researchers Workshop of the Center for Statistics, Bielefeld University
I held a short presentation about our paper Inference on the state process of periodically inhomogeneous hidden Markov models for animal behaviour. We established novel tools to better understand the state process of periodically inhomogeneous hidden Markov models regarding i) the periodically varying unconditional state distribution and ii) the state dwell-time distribution. This was illustrated using the movement track of an elphant from the Ivory Coast. You can download the slides here.

Mitigating consequences of the Markov assumption
24. October 2023, Colloquium of the Center for Statistics, Bielefeld University
I presented the results of my master thesis which focussed on methods for mitigation the undesired consequences of the Markov assumption in hidden Markov models. In particular, I derived properties of the state process of periodically inhomogeneous Markov chains, and extended the model class of hidden semi-Markov models to allow for inhomogeneity in the state dwell-time distributinos. You can download the slides here.

Posters

Mitigating consequences of the Markov assumption
4. December 2023, Doctoral workshop of the Bielefeld Graduate School of Economics and Management (BiGSEM), Bielefeld University
I also presented the results of my master thesis as a poster in the 18. doctoral workshop of the Bielefeld Graduate School of Economics and Management (BiGSEM). You can download the poster here.