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archive.R
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# - [Education](#education)
# - [Publications](#publications)
# - [Teaching](#teaching)
# - [Talks](#talks)
# - [Workshops and Training](#workshops)
# - [Software Contributions](#software)
# - [Skills](#skills)
# - [Peer Reviewer](#reviewer)
# About Me
## Education{#education}
#### current
#
# - **Ph.D. Researcher in Bayesian Statistics** (since 2021)
# - Cluster of Excellence SimTech, University of Stuttgart, Germany
# - Junior Research Group for Bayesian Statistics, Dr. Paul-Christian Bürkner
# - Focus: Bayesian model comparison, probabilistic machine learning, simulation-based inference
# - Tools: R, Python, Stan
#
# #### completed
#
# - **M.Sc. in Data and Computer Science** (2020-2022)
# - University of Heidelberg, Germany
# - Focus: Deep learning, probabilistic machine learning, scientific visualization
# - Master thesis: *Visualization of Distribution and Uncertainty of Posterior Model Probabilities*
# - Tools: Python, C++, Java, OpenGL
#
# - **M.Sc. in Psychology** (2018-2021)
# - University of Heidelberg, Germany
# - Focus: Statistical inference, machine learning, data science, cognitive modeling, organizational behavior
# - Master thesis: *Did you Miss Me? Model Misspecification in Bayesian Parameter Estimation Tasks with Invertible Neural Networks*
# - Tools: R, Python
#
# - **B.Sc. in Psychology** (2014-2018)
# - University of Heidelberg, Germany
# - Focus: Statistical inference, usability, communication techniques
# - Bachelor thesis: *Influence of suggestive questions on usability tests*
# - Tools: R, SPSS
#
#
# ----
#
# ## Publications {#publications}
#
# #### Accepted
#
# - **Schmitt, M.**, Radev, S. T., & Bürkner, P.-C. (accepted). [Meta-Uncertainty in Bayesian Model Comparison](https://arxiv.org/abs/2210.07278). Artificial Intelligence and Statistics (AISTATS) Conference Proceedings. [Code](https://github.com/marvinschmitt/MetaUncertaintyPaper)
#
# #### Preprints in review
#
#
# - **Schmitt, M.**, Bürkner, P.-C., Köthe, U., & Radev, S. T (in review). [Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks](https://arxiv.org/abs/2112.08866). *arXiv preprint*. [Code](https://github.com/marvinschmitt/ModelMisspecificationBF)
#
#
# ----
#
# ## Teaching {#teaching}
#
# - Exercise **Bayesian Statistics and Probabilistic Machine Learning**, University of Stuttgart
# - Teaching assistant | summer term 2022
# - Lecture **Statistics II**, Fresenius University of Applied Sciences, Heidelberg
# - Lecturer | summer term 2022, winter term 2021/22, summer term 2021, winter term 2020/21
# - Exercise **Statistics II**, Fresenius University of Applied Sciences, Heidelberg
# - Lecturer | summer term 2022, winter term 2021/22, summer term 2021, winter term 2020/21
# - Seminar **Introduction to Statistics with R** for PhD researchers, University of Heidelberg
# - Lecturer | winter term 2021/22 | [Course GitHub Repository](https://github.com/marvinschmitt/IntroStatisticsR) | [Course Website](https://marvinschmitt.github.io/IntroStatisticsR/)
# - Exercise **Statistics I**, Fresenius University of Applied Sciences, Heidelberg
# - Lecturer | summer term 2021
# - Seminar **Communication Techniques**, Fresenius University of Applied Sciences, Wiesbaden
# - Teaching Assistant | summer term 2020
# - Seminar **Statistics with R**, Heidelberg University
# - Teaching Assistant | summer term 2020
# - Seminar **Programming with R**, Heidelberg University
# - Teaching Assistant | winter term 2020/21
# - Tutorial **Statistical Inference**, Heidelberg University
# - Tutor | summer terms 2016, 2017, 2018, 2019
# - Tutorial **Descriptive Statistics and Probability Theory**, Heidelberg University
# - Tutor | winter terms 2017, 2018
#
# ----
#
# ## Talks {#talks}
#
# - _AI Office Hours: Where does AI begin?_, Cyber Valley Public Engagement, [Announcement](https://cyber-valley.de/en/events/KI-Sprechstunde-2022-02)
#
# ----
#
# ## Workshops and Training {#workshops}
#
# - Group Coaching, Fresenius University of Applied Sciences, Frankfurt
# - Co-Trainer | 2017 | 1-day workshop
#
# ---
#
# ## Contributions to Open Source Software {#software}
#
# #### Python
#
# - Radev et al. (2020): `BayesFlow`: Available at [GitHub](https://github.com/stefanradev93/BayesFlow)
#
# ----
#
# ## Skills {#skills}
#
# - **Languages:** German (native), English (fluent), French (basic), Latin (5 years, please don't ever ask), Norwegian (basic)
# - **Programming Stack:** Python, R, occasionally: C++, JavaScript, HTML, CSS
# - **Data Science & Statistics:** R (brms, lme4, afex, tidyverse), Python (Tensorflow/keras, PyTorch, sklearn, scipy, numpy, pandas), Stan, SPSS, Excel
# - **Visualization:** R (ggplot2, plotly, rgl, shiny, gganimate), Python (matplotlib, seaborn)
# - **Writing & Documentation:** LaTeX (KOMA, tikZ), Markdown, RMarkdown, Jupyter, sphinx, roxygen, Quarto
#
# ----
#
# ## Peer Reviewer {#reviewer}
#
# - International Conference on Machine Learning (ICML) 2022
# - Artificial Intelligence and Statistics (AISTATS) 2023
#