Data scientist, aerospace engineer, specialized in statistical modeling and uncertainty analysis for reliable system design.

A practice for making reliable model-based predictions

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(Image by Author)
  • the motivation: where are the uncertainties coming from and why they are important?
  • the solution: V&V and IPAC…


An Overview of Fundamental Concepts and Popular Algorithms

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Photo by Brett Jordan on Unsplash


A Walk-Through of The Fundamental Theories And Practical Implementations of The Gaussian Process Model

A Gaussian process plotted in 3D field
A Gaussian process plotted in 3D field
(Image by Author)
  • it performs quite well in small data regime;
  • it is highly interpretable;
  • it automatically estimates the prediction uncertainty.


This post will walk you through a complete uncertainty analysis case study using Latin Hypercube sampling, Monte Carlo simulation, and hypothetical outcome plots.

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Photo by Paweł Czerwiński on Unsplash


A complete case study with a Gaussian Process model

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Photo by nine koepfer on Unsplash


Hands-on Tutorials

A step-by-step guide to sharpening your skills in creating and displaying animations in Jupyter Notebook.

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Photo by lan deng on Unsplash


Use animations to present the uncertainty vividly

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Photo by Riho Kroll on Unsplash


Optimizing a complex function involves iterative steps to finally reach the global optimum.
Optimizing a complex function involves iterative steps to finally reach the global optimum.
Fig. 1 Optimizing a complex function. (Image by Author)


Getting Started

Wondering how joint, marginal, conditional distributions and Bayes’ rule are connected? Check this illustrative post to connect the dots.

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Fig. 1 Table of Content. (Image by Author)


Hands-on Tutorials

The one article you need to understand the most useful probability concepts

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Fig. 1 Table of content. (Image by Author)

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