Hello my names Harrison Curtis (coding cowboy). I am a former Data scientist and quantitative methodologist at University of Reading EBRlab 2020/2023. Working primarily on the Bayesian workflow for psychometrics/item response theory, see, as well as fMRI and EEG timeseries analysis, see, and how these methods could be implemented in the current analytical landscape dominated by "old school" methods. Recently I have put a heavy focus on cutting edge developments in predictive inference using Machine learning methods. I am Looking forward to apply what I have learned and applied outisde of academia in industry.
When I am not coding im working with my hands π¨ or dancing πΊπ».
- Python, R, Jullia, SQL, Matlab.
- Casual/Predictive inference,
- Questionaire and Survey generation.
- Python: Numpy, Scipy, Pandas, Matplotlib, Seaborn, Scikit-learn, Statmodels PyMC, Numpyro, PyStan.
- R: LME4, MGCV, lavaan/blavaan, Tidyverse/Tidymodels, brms, Rstan, easystats. RINLA.
- Julia: MixedModels, Turing.
- SQL: Postgres, MySQL, SQLlite.
- Matlab: psychopy, palamedes toolbox.
- Cloud computing with AWS and Microsoft Azure
- HTML/CSS/Javascript for web development
- C
- Rust
How to reach me: Linkedin