Måns Magnusson
Associate Professor
Greater Stockholm Metropolitan Area Sweden
Summary
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Rockstar🎓
Top SchoolMåns Magnusson is an associate professor and Bayesian statistician based in the Greater Stockholm area with 13 years of experience bridging academic research, government statistics, and applied data science. His work spans Bayesian modeling, topic-model integration of textual data, time series and survey methodology, and practical public-sector statistics production. He contributes to open-source projects—such as Bayesian Data Analysis course materials and COVID-19 modelling code—focusing on reproducible R implementations, visualization fixes, and testing. Having progressed from national statistical agencies to academic leadership, he brings rare domain depth in official statistics combined with hands-on computational skills. Colleagues value his ability to translate complex statistical methods into teachable materials and production-ready code.
13 years of coding experience
7 years of employment as a software developer
Ph.D., Statistics, Ph.D., Statistics at Linköpings universitetMaster of Science (MSc), Statistics, Master of Science (MSc), Statistics at Stockholms universitet
Swedish, English, French
Github Skills (9)
data-visualizations10
data-visualization10
data-visualisation10
bayesian10
statistical-models10
r10
bayesian-inference9
testing9
bayesian-methods8
Programming languages (16)
Github contributions (5)
avehtari/BDA_course_Aalto
Sep 2018 - Jul 2020
Bayesian Data Analysis course at Aalto
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:135 commits, 51 PRs, 34 pushes in 1 year 9 months
Contributions summary:Måns primarily contributed to a Bayesian Data Analysis course at Aalto. Their commits demonstrate the addition and modification of R code, including defining a t-distribution function and integrating tests for statistical exercises. Furthermore, the user appears to be integrating external contributions, such as merging branches and updating the course materials to reflect new requirements. These contributions span a range of tasks, from writing R code and tests to incorporating external updates from other users.
aaltostatisticsdata-analysisbayesian-inferencebayesian
ImperialCollegeLondon/covid19model
Apr 2020 - Apr 2020
Code for modelling estimated deaths and cases for COVID19.
Role in this project:Data Scientist
Data ScientistContributions:14 commits, 3 PRs, 9 comments in 5 days
Contributions summary:Måns primarily focused on modifying and adding plotting code related to the COVID-19 model. They fixed bugs in existing plot code, including issues with date formatting and deprecated functions. They also initialized and updated several model files, and debugged the model. Their contributions appear centered on visualization and potentially model debugging aspects of the project.
casespythondeathsmachine-learningestimated
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