Main Focus

  • statistical modeling
  • reproducible research workflows
  • machine learning for nested/hierarchical data
Technical Skills
  • data analysis in R, Julia, and Python
  • developing software with version control, unit tests, and continues integration
  • typesetting in Latex, HTML and CSS

Curriculum Vitae

Education

2020-now Pre-doctoral research fellow (Max Planck Institute for Human Development)

  • Topic: “Towards individualised prediction of behaviour: A widely applicable learning procedure for hierarchical data.”
  • Supervisors: Dr. Andreas M. Brandmaier

2018-2020 M.Sc. Psychology (Humboldt-Universität zu Berlin)

  • Grade 1.1 (very good)
  • Track: Psychological Research Methods and Diagnostics
  • Thesis: “Automatic Reproducibility made simple: Automating reproducible research workflows”
  • Supervisors: Prof. Manuel Voekle, Dr. Andreas M. Brandmaier (grade 1.0)

2015-2018 B.Sc. Psychology (Humboldt-Universität zu Berlin)

  • Grade 1.5 (very good)
  • Thesis: “Data Driven Development Diagnostics”
  • Supervisors: Prof. Matthias Ziegler, Dr. Martin Hecht (grade 1.0)

2009-2015 Abitur (Gymnasium Villa Elisabeth)

  • Grade 1.2
Academic Track

2019-2020 Student Research Assistant (Formal Methods in Lifespan Psychology | Max Planck Institute for Human Development)

2018 Student Research Assistant (Emmy Noether Research Group “Adaption to major life events”)

2017-2019 Student Research Assistant (Department of Diagnostics | Humboldt-Universität zu Berlin)

Experiences

2017 Internship (ROC Institute GmbH)

  • developing and implementing production ready machine learning algorithms to determine most profitible human resource interventions on individual and group level

2015-2016 Product Owner/Startup Founder (ShareLock)

  • leading prototype development
  • supervision of small team (front-end & back-end developer, system architect, designer)
Honors and Funding

2019-2020 Scholarship (German Academic Scholarship Foundation “Studienstiftung”)

2014 “Jugend forscht” Award (regional—informatic/mathematics)

Peer-reviewed Journal Articles
  1. Van Lissa, C. J., Brandmaier, A. M., Brinkman, L., Lamprecht, A.-L., Peikert, A., Struiksma, M. E., & Vreede, B. M. I. (2021). WORCS: A workflow for open reproducible code in science. Data Science, (in press), 1–21. https://doi.org/10.3233/DS-210031

  2. Peikert, A., & Brandmaier, A. M. (2019). A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker. Quantitative and Computational Methods in Behavioral Sciences, (in press). https://doi.org/10.31234/osf.io/8xzqy

  3. Ziegler, M., & Peikert, A. (2018). How Specific Abilities Might Throw “g” a Curve: An Idea on How to Capitalize on the Predictive Validity of Specific Cognitive Abilities. Journal of Intelligence, 6(3), 41. https://doi.org/10.3390/jintelligence6030041

Conference Talks
  1. Ziegler, M., & Peikert, A. (2021, July 12). Artificial Intelligence and Psychological Assessment: Between Revolution and Reality. Accepted for ITC Colloquium 2021.

  2. Peikert, A., & M. Brandmaier, A. (2021, May 18). Reproducibility in Big Data with the repro package. Accepted for Research Synthesis & Big Data Conference 2021.

  3. Ziegler, M., & Peikert, A. (2019, September 17). Symposium “Challenges in and Approaches to Behavioral Assessment & Prediction”. DPPD 2019.

Teaching

29.03.2020 Two-day workshop on Reproducible Research (Universitätsklinikum Hamburg-Eppendorf/Universität Hamburg)

  • academic writing in Rmarkdown
  • collaboration via GitHub Pull Requests and Code Review

18.03.2021 Half-day workshop on Docker and Make (Max Planck Institute for Human Development)

20.02.2020 Full-day workshop “Reproducibility” with Andreas Brandmaier (Max Planck UCL Centre for Computational Psychiatry and Ageing Research)

  • collaboration via GitHub Pull Requests
Software
  1. Peikert, A., Brandmaier, A. M., & van Lissa, C. J. (2021). Repro: Automated setup of reproducible workflows and their dependencies [Manual]. https://github.com/aaronpeikert/repro

  2. van Lissa, C. J., Peikert, A., & Brandmaier, A. M. (2021). Worcs: Workflow for open reproducible code in science [Manual]. https://CRAN.R-project.org/package=worcs

Invited Research Visits

17.01.2020 Talk on Reproducible Research (Universität zu Lübeck)

Volunteering

2020-now Statistical Consultant (Methods Group Berlin, Humboldt Universität zu Berlin)

2019-now Coorganizer of “μΣ” Reading Club on Statistical Modelling and Philosophy of Science (pmOne Group)

2019-now Two-year Collaborative Project on Information Theory (German Academic Scholarship Foundation “Studienstiftung”)

2017-2019 Representing the student body in: (Humboldt-Universität zu Berlin)

  • three habilitations
  • two appointment processes
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