OLIVER
ZINGG
Psychologist and data scientist, Zürich sector. I design the study, model the data and explain what it means. M.Sc. Applied Information & Data Science, HSLU — December 2026.
FOR HIRE
CASE FILES
12 files on record. Showing the priority cases.
Learning and memory formation in children and adolescents with psychiatric disorders
EEG data from children and adolescents with various psychiatric disorders, analysed with linear mixed-effects models to track successful learning. Graded 6.
Support vector machines vs. CNNs for Alzheimer's disease classification
A systematic review comparing classical machine learning and deep learning for classifying Alzheimer’s disease from MRI images. Graded 6.
Simpson's paradox and mixed-effects models
Visualising Likert scales
Interactive presentations with Quarto
MISSION LOG
Education above the line. Field work below.
// COMBAT STATS
// INVENTORY
- Power BI
- Tableau
- SPSS
- Excel
- Quarto
- RStudio
- LaTeX
- Markdown
// LANGUAGE MODULES
- German — bilingual
- English — bilingual
- French — intermediate
Certs: Advanced Learning Algorithms · Supervised Machine Learning: Regression and Classification (DeepLearning.AI & Stanford)
DATABANK
Personal knowledge base. 18 entries, 5 directories.
INCOMING TRANSMISSION?
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▶ EMAIL OLIVER9402@GMAIL.COMOliver
Zingg
Psychologist and data scientist in Zürich. I design the study, model the data and explain what it means. M.Sc. in Applied Information and Data Science at HSLU, December 2026.
Two tracks, one path.
Six years of psychology and a data science degree, alongside market research, insights and analytics work.
The work, the notes,
the path.
Learning and memory formation in children and adolescents with psychiatric disorders
Support vector machines vs. CNNs for Alzheimer's disease classification
Simpson's paradox and mixed-effects models
Visualising Likert scales
Interactive presentations with Quarto
Statistics
Statistical modelling and machine learning, from confidence intervals to graph neural networks.