Teaching

We teach courses for the Master's in Data Science at the University of Helsinki, organize workshops and tutorials in statistical model fitting, and provide other teaching material such as a guide to writing Master's theses.

Taught Courses at the University of Helsinki

Ongoing courses (academic year 2024/25)

  • Computational Statistics (MAST32001). Period I, Autumn term. Taught yearly from Autumn 2021. . (2024 edition co-taught with Dr. Martin Jørgensen.)
  • Computational Statistics, self-study version (MAST32001). Period III-IV, Spring term, online teaching. Taught yearly from Spring 2022. .
  • Probabilistic Cognitive Modelling (DATA20047). Period III, Spring term. Taught yearly from Spring 2023. .
  • Seminar on Generative AI (DATA20056). Period I, Autumn term. . (Co-taught with Dr. Nasrulloh Loka and Dr. Paul Chang)

Past courses

  • Spring 2022, period III: "Computational Cognitive Neuroscience" (, ; co-taught with )
  • Spring 2021, period III-IV: “Seminar on Probabilistic Intelligence in Brains and Machines” (, )

Guide to Writing Master's Theses

I wrote a , mostly targeted at (my) students of the of the University of Helsinki—but possibly of broader interest.

International Tutorials and Workshops

We have been regularly giving classes, tutorials, and workshops at summer schools and for research groups at various institutions worldwide, for a duration that ranges from 20 minutes to 4+ hours. Typical topics include optimization (and our toolbox), Bayesian model fitting (and our toolbox), and model comparison.

As representative examples:

  • The module on computational modeling and statistical model fitting taught at the University of Geneva in Spring 2020, as part of the graduate course Trends in Computational Neuroscience. Slides and Python notebook ().
  • Lectures on optimization and Bayesian inference for statistical model fitting given in 2022 at the Barcelona summer school for Advanced Modeling of Behavior (). Slides and MATLAB code ().

We also like to play around with visualizations for demonstration purposes. This is a demo we built of several optimizers at work ().

 

List of past workshops:

  1. Joint Ma-Niv-Pillow lab meeting, Princeton University (Princeton, NJ, Sep 2015).
  2. , New York University (New York, NY, May 2016).
  3. , University of Geneva (Geneva, Switzerland, Sep 2016).
  4. , Northwestern University (Chicago, IL, Jun 2017).
  5. , Baylor’s College of Medicine (Houston, TX – in telepresence, Jul 2017).
  6. , University of Minnesota (Minneapolis, MN, Aug 2017). Code:
  7. , New York University (New York, NY, Sep 2017).
  8. , University of Minnesota (Minneapolis, MN, Aug 2018). Code:
  9. , University of Bristol (Bristol, UK, May 2019). Code:
  10. , Columbia University (New York, NY, Sep 2019).
  11. Center for Neural Science, New York University (New York, NY, Sep 2019). Code:
  12. Psychology department, Stockholm University (Stockholm, Sweden, Nov 2019).
  13. Trends in Computational Neuroscience graduate course; Department of Neuroscience, University of Geneva (Geneva, Apr 2020). Website:
  14. IBL Computational Neuroscience course, International Brain Laboratory (Apr 2020).
  15. , Barcelona Biomedical Research Park (Barcelona, Spain, Sep 2022). Code: