Forschungsinteressen
- 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
Vita
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
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
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
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
Ziegler, M., & Peikert, A. (2021, July 12). Artificial Intelligence and Psychological Assessment: Between Revolution and Reality. Accepted for ITC Colloquium 2021.
Peikert, A., & M. Brandmaier, A. (2021, May 18). Reproducibility in Big Data with the repro package. Accepted for Research Synthesis & Big Data Conference 2021.
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
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
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