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Rickard Karlsson

PhD candidate in causal inference & machine learning
Delft University of Technology, the Netherlands

About me

I am a third-year PhD candidate at TU Delft supervised by Jesse Krijthe and Marcel Reinders in the Pattern Recognition Laboratory. During my PhD have I also been fortunate to spend time at Harvard University in the CAUSALab working with Issa Dahabreh.

My research interests are at the intersection of causal inference and machine learning, with the goal of creating more robust and reliable methods for predictions and decision-making from data. Most recently, I have been interested in how to combine datasets from different sources, such as different studies or experiments, to improve the validity and statistical inference of causal analyses.

Originally, I come from Sweden where I finished my BSc in physics and MSc in mathematics at Chalmers University of Technology. I also got the opportunity to do an internship at NASA Goddard Space Flight Center during my studies. My full CV can be found here. And when not doing research, I enjoy hiking, photography, and CrossFit.

News

  1. [Oct 2023] Paper accepted to NeurIPS 2023 workshop on Causal Representation Learning. You can read it here.
  2. [Sep 2023] Paper accepted to NeurIPS 2023: Detecting hidden confounding in observational data using multiple environments.
  3. [Sep 2023] Starting my research visit at Harvard University in the CAUSALab to work with Issa Dahabreh this semester.
  4. [Aug 2023] Paper on benchmarking surrogate-based optimation algorithms from my masters accepted to Applied Soft Computing. You can read it here.
  5. [Apr 2023] Attended CLEAR 2023 in beautiful Tübingen, Germany.
  6. [Oct 2022] Gave an invited talk to the statistics group at TU Eindhoven about my work on detecting hidden confounding. [slides]
  7. [Sep 2022] Presented a poster at the ELLIS Doctoral Symposium in Alicante, Spain.
  8. [Jun 2022] Presented a poster at the Machine Learning Summer School 2022 in Krakow, Poland.
  9. [Jan 2022] Paper accepted to AISTATS 2022: Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models.
  10. [Sep 2021] Leaving Sweden to start my PhD at Delft University of Technology.
  11. [Jul 2021] Got 1st place on the GECCO 2021 Industrial Challenge (limited evaluation track) together with Laurens Bliek and Arthur Guijt, our approach is described here.
  12. [Jun 2021] Finished my thesis and graduated with a MSc in Engineering Mathematics from Chalmers University of Technology.
  13. [Nov 2020] Paper accepted to BNAIC/BeneLearn 2020: Continuous surrogate-based optimization algorithms are well-suited for expensive discrete problems.

Publications

The list of publications can also be found on my Google scholar profile.

  • Rickard Karlsson, Jesse H. Krijthe Detecting Hidden Confounding in Observational Data using Multiple Environments. NeurIPS, 2023.
    [paper] [code]
  • Rickard Karlsson, Ștefan Creastă, Jesse H. Krijthe Putting Causal Identification to the Test: Falsification using Multi-Environment Data. Causal Representation Learning Workshop, NeurIPS, 2023.
    [paper]
  • Laurens Bliek, Arthur Guijt, Rickard Karlsson, Sicco Verwer, Mathijs de Weerdt Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions. Applied Soft Computing, 2023.
    [paper] [code]
  • Rickard Karlsson*, Martin Willbo*, Zeshan Hussain, Rahul G. Krishnan, David Sontag, Fredrik D. Johansson Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models. AISTATS, 2022. *Equal contribution
    [paper] [code]
  • Rickard Karlsson, Laurens Bliek, Sicco Verwer, Mathijs de Weerdt Continuous Surrogate-based Optimization Algorithms are Well-suited for Expensive Discrete Problems. BNAIC/Benelearn, 2020.
    [paper]

Contact

You can contact me through email at r.k.a.karlsson{at}tudelft.nl, feel free to reach out for collaborations. I am also active on X (former Twitter).

Office


Room 6.E.040, Building 28 at Delft University of Technology
Van Mourik Broekmanweg 6, 2628 XE Delft, The Netherlands