Enterprise AI
RAG applications, prompt engineering, automated LLM evaluation and front-end delivery at CGI SmartLab.
Applied AI and Machine Learning Engineer
Reliable AI, from research questions to working systems.
End-to-end AI applications, forecasting and uncertainty, explainable machine-learning
Forecasting
Time-series modelling, validation and uncertainty estimation with conformal predictions at Predikt.ai.
Explainable ML
Extended explainability toolboxes to time-to-event data with partial information (censoring), and created novel explainability toolbox for Random Forest predictions (Bellatrex).
Current work
I am a Data Scientist at CGI SmartLab. I contribute across an enterprise AI application, from retrieval and system-prompt behaviour to automated evaluation of LLM alignment and React front-end features. The work calls for both technical breadth and the ability to translate open-ended stakeholder needs into testable improvements.
Previously, as an AI Research Engineer at Predikt.ai, I translated forecasting problems into technical specifications and structured experiments. I developed and benchmarked forecasting approaches, improved model accuracy through regularisation, and worked with conformal prediction methods to estimate uncertainty.
Selected work
Bellatrex
An explainable-AI method and maintained Python package for extracting representative rules from Random Forest ensembles. The research was evaluated across 89 datasets and published in IEEE Access.
IntervalSHAP
A compact approach to feature attribution for time-to-event predictions, focused on explanations over selected time intervals.
EDGEHOG
A computer-vision workflow for reproducible, high-throughput measurement of fibre directionality and dispersion in biomedical images.
See the full selected-work page →
Background
I hold a PhD from KU Leuven, where I developed explainable-AI and active-learning methods for survival analysis and collaborated with clinical and scientific teams. That research remains useful evidence of how I design experiments, validate models and communicate across disciplines, but my professional direction is applied AI and product-oriented R&D outside academia.
My Google Scholar profile and dissertation contain the full research record.
Beyond the job title
I am a mathematician by training, a multilingual European, and an enthusiastic language learner. I enjoy mentoring, collaborating across technical and domain boundaries, and making complex ideas easier to use.