Resume

Head of Machine Learning, Faktion

2021-Present

I’m leading a team of amazing ML engineers on a mission to bring value to our customers using data. We use Computer Vision, Reinforcement Learning, and Natural Language Processing to reach that goal. I work closely with our HR team to recruit the best talent.

Machine learning engineer & head of ML education, Faktion

2018-2020

Datacamp instructor for two courses reaching >18K students:

• Dimensionality reduction in Python
• Reshaping data with tidyr

Intro to ML course:

• Full day Machine Learning 101 Using Python workshop at the 2019 MLConference in Berlin.

Sensor data analysis:

• Building condition classifiers for high throughput telemetry sensor data.
• Setting up machine learning pipeline within lambda architecture.
• Anomaly detection pipeline for well-being of elders using infra-red motion sensors.
• Forecasting electricity and natural gas usage for hundreds of customers.
• Yield optimization and root-cause analysis of an industrial polymerization process.

Sales analytics:

• Product recommendation engine
• Time series forecasts (ARIMA)
• Customer segmentation
• Propensity model

Computer vision:

• Damage detection on air freight containers.
• Solar panel detector from aerial images (Dockerized PostgreSQL + PostGIS database for aerial image pre-processing -> Microsoft Azure custom vision API)
• Winner of the 2018 Vinci Energies Hackathon detecting emergency situations from video data

Consulting:

• AI maturity assessment
• AI strategy development

Data Scientist, MCS solutions

2015-2018

Sensor data analysis:

• Combining data sets from multiple sources (Hadoop, Oracle, local files (xml, csv, json, excel…))
• Building R-packages
• Tailoring visualizations for any data set
• Building interactive dashboards
• Getting actionable insights from data and report to clients
• Setting up logging and email alerts for scheduled analyses
• Forecasting comfort conditions (CO2, temperature, humidity)
• Forecasting battery drainage
• Applying a range of machine learning techniques (Random forests, GLM, PCA, Clustering, regression, Anomaly detection,…) + Experiment with neural nets

Custom analyses:

• Vulnerability assessment of global supply chain
• Optimize office layout based on employee activities
• Geo-tagging addresses and spatial analysis
• Survey analysis

PhD student, Ghent University

2011-2015

Building complex individual-based Monte Carlo models in a spatial context (using Python) and run them on High Performance Computing infrastructure. Scientific writing and talks. Mentoring students during their Master thesis and teaching. International collaborations.