Stefan Radev

Stefan Radev, M.Sc.

Stefan Radev, M.Sc.

University of Heidelberg
Institute for Psychology
Hauptstrasse 47-51 – Room F040
69117 Heidelberg

Primary Advisor:  Prof. Dr. Andreas Voss (University of Heidelberg)

Additional Supervisors: Prof. Dr. Thorsten Meiser, Prof. Jeffrey Rouder, Ph.D.

Dissertation Proposal: Pushing the boundaries: Tackling intractable response-time models with deep learning methods

  • Research Areas

    • Machine Learning & Deep Learning
    • Bayesian Methods for Parameter Estimation and Model Comparison
    • Mathematische Modelle
    • Neurofeedback
  • Teaching (SMIP)

    • Workshop „Python Basics“ (together with Ulf Mertens)
  • Publications

    Wieschen, E. M., Voss, A., & Radev, S. (2020). Jumping to Conclusion? A Lévy Flight Model of Decision Making. The Quantitative Methods for Psychology, 16(2), 120–132. https://doi.org/10.20982/tqmp.16.2.p120

    Radev, S. T., Mertens, U. K., Voss, A., & Köthe, U. (2019). Towards end‐to‐end likelihood‐free inference with convolutional neural networks. Br J Math Stat Psychol. doi:10.1111/bmsp.12159

    Mertens, U. K., Voss, A., & Radev, S. (2018). ABrox—A user-friendly Python module for approximate Bayesian computation with a focus on model comparison. PLOS ONE, 13(3), e0193981. https://doi.org/10.1371/journal.pone.0193981

  • Posters

    Radev, S.T., Mertens, U., Voss, A. (2018). Abrox - a graphical user interface for approximate Bayesian computation. In: 60. Tagung experimentell arbeitender Psychologen. Marburg, Germany.

    Radev, S. T., Lerche, V., Mertens, U., & Voss, A. (July 2017). Diffusion model analysis: a graphical user interface with fast-dm. Poster presented at the „50th Annual Meeting of the Society for Mathematical Psychology (MathPsych)“ 2017 in Warwick.

    Radev, S. T., Lerche, V., Mertens, U., & Voss, A. (September 2017). Diffusion model analysis: a graphical user interface to fast-dm. Poster presented at the „13. Tagung der Fach­gruppe Methoden & Evaluation der Deutschen Gesellschaft für Psychologie (FGME)“ 2017 in Tübingen.

    Radev, S.T. (2019, June). Taming the Intractable: Deep Learning for Universal Parameter Estimation. Poster at the 34th IOPS/SMiP Summer Conference, 13-14 June 2019, Utrecht, Netherlands.