Statistical Modeling Blogs

2/7/2026 • EN

Dan Simpson

Dan Simpson is a technical writer and researcher focusing on C++, JAX, and advanced statistical computing. His blog dives deep into sparse matrices, autodiff, Bayesian methods, and modern AI techniques, blending theory with practical, hands-on implementations.

statistical computing sparse matrices autodiff

Dan Simpson

18

2/3/2026 • EN

Noam Ross

Noam Ross is a research software engineer and data scientist writing about open-source software, reproducible research, and the ethics of technology. His blog explores tooling choices, CI/CD workflows, and the social impact of software in scientific work.

open source research software reproducible science

Noam Ross

36

2/2/2026 • EN

Jake VanderPlas

Jake VanderPlas is an astronomer and open-source leader, serving as Director of Open Software at the University of Washington’s eScience Institute. He writes and builds widely used Python tools for data science, machine learning, and scientific computing.

python data science machine learning

Jake VanderPlas

66

1/28/2026 • EN

Jakub Nowosad

Jakub Nowosad is a computational geographer and Associate Professor at Adam Mickiewicz University, also serving as a Visiting Scientist at the University of Münster. He develops open-source tools and spatial methods for reproducible, scalable environmental and ecological analysis, and co-authors Geocomputation with R and Geocomputation with Python.

geocomputation spatial analysis environmental modeling

Jakub Nowosad

43

1/28/2026 • EN

Andrew Heiss

Andrew Heiss is a researcher and educator focused on data visualization, causal inference, and applied statistics using R and Bayesian methods. He writes extensively about reproducible research, GIS, and analytical workflows, and teaches data science and social science methods.

data visualization causal inference R programming

Andrew Heiss

55

1/26/2026 • EN

Emir U

SEO Short Description (2–3 lines): Emir U. is a research-focused software engineer applying mathematics, statistics, and computer science to real-world problems, with 18+ years in software and 7+ years in commercial research. A PhD candidate in astronomy with a background in applied maths and philosophy, he writes about machine learning, logic, and statistical modeling.

data science research applied statistics machine learning methods

Emir U

25

1/25/2026 • EN

Andis Ariet

Andis Arietta is a data scientist and evolutionary ecologist researching how land management and climate change shape eco-evolutionary dynamics. With a background in genomics, statistics, and machine learning, he bridges science, conservation, and data-driven decision making.

Data Science Evolutionary Ecology Machine Learning

Andis Ariet

7

1/25/2026 • EN

Thomas Lumley

Thomas Lumley writes thoughtful, in-depth articles on statistics, data analysis, and statistical modeling. His blog explores topics like survey methods, regression, simulations, and inference with a rigorous yet reflective approach.

statistics data analysis statistical modeling

Thomas Lumley

215

1/23/2026 • EN

Stern Semasuka

Stern Semasuka is a data scientist at WestJet who writes beginner-friendly guides on machine learning, data analysis, and programming. His blog simplifies complex ML concepts using practical projects and the Feynman Technique.

machine learning data science beginner tutorials

Stern Semasuka

10

1/2/2026 • EN

John D. Cook

John D. Cook provides expert consulting in applied mathematics and data privacy, helping clients from tech, biotech, and legal industries—including Amazon, Google, Microsoft, and Amgen—solve complex problems efficiently.

applied mathematics data privacy consulting

John D. Cook

76