Christoph Bamberg
Greetings and welcome to my webpage, I'm Christoph.
You can find an overview of my skills and experience here.
Please refer to my CV for details.
CV & Contact
- Linkedin: Christoph Bamberg
- My CV.
- Mastodon: @ChristophB@fediscience.org
- GitHub: ChristophBg
Publications
- ORCiD profile: A list of my publications
- OSF profile: My ongoing projects
- Most recent publication: The impact of dietary claims on behaviour: Expectations qualify how actual satiety affects cognitive performance.
Scientific Outreach
- Wrote a column for "Spektrum der Wissenschaft", the German Scientific American on breakfast, Intermittent Fasting and concentration.
- In Mind Blog. Wrote a blog article on the importance of breakfast for concentration. (also available in German).
- Pint of Science Salzburg 2024. Co-organising the Pint of Science Festival in Salzburg in 2023 and 2024.
- Learning Bayesian Statistics Podcast. Contributing to a podcast on Bayesian statistics.
- Scientists for Future Austria blog and press release (both in German).
Experience
- Scientific programming using Python and R.
- Analysis of behavioural data, EEG data and various physiological measures.
- Some teaching (e.g. as a tutor for logic and scientific methods).
Skills
- Python: anything from programming experiments over data analysis to text-parsing, mostly using functional programming.
- R: preferrably Bayesian statistics.
- SQL: for business data analystics.
Hobbies
- Playing Jazz guitar, organising jam-sessions.
- Hiking along the rivers of Germany and mountains of Austria.
- Improving my freestyle swimming technique.
Blog
- A guide for DAGs and Bayes with EMA data: I go through a workflow combining Directed Acyclical Graphs with Bayesian analysis for Ecological Momentary Assessment data.
- A guide for multi-level correlation in R using STAN: I use simulated nested data to show the benefit of multi-level correlations and how these can be written in STAN.
- DAG & Generative model. I made a Directed Acyclical Graph and wrote a generative model for a preregistration.
I later used these models to simulate data from and hope that the workflow might be interesting for others too.
Find the preregistration here: osf.io