About me

Experience and education

Lecturer in Statistics & Data Science @ KULeuven with previous experience in BI/data science consulting with projects related to retail and marketing analytics, big data and machine learning applications.
Specialized in Data Visualization, Statistics & Natural Language Processing.
Living in Belgium, and passionate about football and travelling.

Biostatistics doctoral degree by Catholic University of Leuven
Statistics master degree by Catholic University of Leuven
Mathematics bachelor degree by Hasselt University
Data Science Bootcamp certification by Keyrus NV
Curriculum Vitae

Projects and research

Professional and academic experiences

Market Basket analysis

Analyse which products are bought together in retail

Sentiment analysis on RW15

Analyse which bands and stages of RW15 scored high on twitter

Route optimization

Optimize routes based on statistical clustering principles

Euro 2016 prediction

Predict the chances of every team with advanced analytics

Statistics & data science courses

KU Leuven and FLAMES courses

Basic Parametric Statistics

Course about the basics of Parametric Statistics

Fundamental Concepts of Statistics

Course about the theoretical concepts of Statistics

Data Visualisation with R Shiny

Course about the principles of R Shiny

Data Visualisation with Shiny for Python

Course about the principles of Shiny for Python

Clustering Analysis for data science

Course about basic clustering techniques

Classification with Logistic regression

Course about logistic regression

Python Fundamentals

Seminar on the essentials of the Python infrastructure

Containerisation with Docker & Kubernetes

Course on containerisation with Docker & Kubernetes

Text Mining

Course about Text mining techniques

Monte Carlo simulation

Chapter (in Dutch) about Monte Carlo simulation (Chapter 3)

Machine Learning

Course about unsupervised, deep, and reinforcement learning

Hugging Face

Seminar on the infrastructure and usage of Hugging Face

Cloud computing

Course about the fundamentals of Cloud computing, with focus on AWS

Sufficientië in exponentiële families

Seminar (in Dutch) about the theoretical principle and application of sufficiency

   

Presentations, posters & news articles

External contributions

Leuven Statistics Days 2016

Presentation on "Negative variance components in an underdispersed, clustered time-to-event setting"

ENAR 2018 Spring Meeting

Presentation on "A Weibull-count apprach for handling under- and/or overdispersed clustered data structures"

2019 Joint Statistical Meetings

Presentation on "A flexible finite mixture model family for analyzing underdispersed discrete data, with negative weights"

ISCB 2020

Poster on "A Weibull-count approach for handling overdispersed longitudinal data on epileptic patients"

2022 International Conference on Teaching Statistics

Presentation on "FLAMES (Flanders training network for methodology and statistics): A longitudinal analysis of our doctoral training initiative"

Impact of AI on KU Leuven

Newsarticle on "90% van de studenten gebruikt AI: Tijd voor nieuwe evaluatievormen?"

Doctoral & Masterthesis

KU Leuven

Doctoral thesis

Title: Principled hierarchical models for dealing with correlated, overdispersed, and/or underdispersed data

Masterthesis

Title: Exploration of Extended Models for Overdispersed, Repeated Time-to-Event Data

Contact details

Ways to get in touch:

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