Recent Posts

Quantifying the Expected Value of Information

TLDR We sometimes have the option to purchase additional information (like paying for an experiment to be performed, or for a report from an expert consultant) to help us in problems of decision making under uncertainty.
Last updated on Aug 3, 2020 30 min read Bayesian Decision Analysis, Hugin, Uncertainty, VoI, R

Maximum Likelihood Estimation

TLDR Maximum Likelihood Estimation (MLE) is one method of inferring model parameters. This post aims to give an intuitive explanation of MLE, discussing why it is so useful (simplicity and availability in software) as well as where it is limited (point estimates are not as informative as Bayesian estimates, which are also shown for comparison).
Jul 28, 2020 13 min read Parameter Estimation, Maximum Likelihood, R, Python, SciPy, Stan

Why Go Bayesian?

TLDR This post is intended to be a high-level discussion of the merits and challenges of applied Bayesian statistics. It is intended to help the reader answer: Is it worth me learning Bayesian statistics?
Mar 24, 2020 7 min read Bayesian, Uncertainty, Decision Analysis

Bayesian Logistic Regression with Stan

TLDR Logistic regression is a popular machine learning model. One application of it in an engineering context is quantifying the effectiveness of inspection technologies at detecting damage. This post describes the additional information provided by a Bayesian application of logistic regression (and how it can be implemented using the Stan probabilistic programming language).
Feb 15, 2020 17 min read Bayesian, MCMC, Scikit-Learn, R, Stan, Logistic Regression

Animating Plots

TLDR There are many instances where it may be useful to animate graphical representations of data, perhaps to add an additional dimension to a plot. The below example builds a cumulative map of car accidents in the UK using some of the functionality of the gganimate package.
Jun 4, 2019 5 min read R, gganimate, ggplot2, dplyr
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Recent Publications

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Domenic Di Francesco, Michael Havbro Faber, Marios Chryssanthopoulos, Ujjwal Bharadwaj
December 2020 Vol. 204C
Consistent and Coherent Treatment of Uncertainties and Dependencies in Fatigue Crack Growth Calculations using Multi-Level Bayesian Models

Consistent and Coherent Treatment of Uncertainties and Dependencies in Fatigue Crack Growth Calculations using Multi-Level Bayesian Models

Bayesian multi-level modelling for partial pooling of information between fatigue crack growth test datasets.
Project Journal Website
Domenic Di Francesco, Michael Havbro Faber, Marios Chryssanthopoulos, Ujjwal Bharadwaj
August 2020 In OMAE2020
Bayesian Multi-Level Modelling for Improved Prediction of Corrosion Growth Rate

Bayesian Multi-Level Modelling for Improved Prediction of Corrosion Growth Rate

Partial pooling of inspection information from multiple locations to improve probabilistic estimates of corrosion growth rate.
Project Conference Website
Domenic Di Francesco, Michael Havbro Faber, Marios Chryssanthopoulos, Ujjwal Bharadwaj
December 2019 In IFED2019
Inspection Planning of Hazardous Locations Using a Value of Information Analysis

Inspection Planning of Hazardous Locations Using a Value of Information Analysis

Extension of Bayesian decision theoretic framework to account for risk of inspection activities in quantifying the expected value of information.
Project Conference Website
Domenic Di Francesco, Michael Havbro Faber, Marios Chryssanthopoulos, Ujjwal Bharadwaj
September 2019 In IPW2019
Bayesian Fatigue Modelling

Bayesian Fatigue Modelling

Quantifying the variability within, and the inter-dependency between all parameters in models that predict fatigue failure of welded steel structures.
Project Conference website

CEng, PhD Candidate

NSIRC

Biography

My research interests include multi-level Bayesian modelling (for partial pooling of information) and it’s decision theoretic applications, such as quantification of the expected value of information. I also work in football (soccer) analytics.

Interests

  • Bayesian Statistics
  • Information Theory
  • Fracture and Fatigue of Materials
  • Decision Analysis
  • Football Analytics

Popular Topics

Bayesian Bayesian Data Analysis Bayesian Decision Analysis Bayesian Modelling Bayesian Statistics Corrosion Growth Decision Analysis Deep Learning Demo dplyr Fatigue Crack Growth Fracture & Fatigue gganimate ggplot2 Hugin Information Pooling Markov Chain Monte Carlo Sampling R Stan Uncertainty

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