I’ve been programming since I was ten, and I’ve worked with neural networks since 2015 (seven years before ChatGPT). For example, in my master’s thesis, I trained a recurrent neural network that significantly improved on the state of the art in real-time event detection in brain signals. These days I mostly direct AI agents, both for coding and for research. I’ve lived every step change in LLM agent capability up close. I enjoy learning new things and do so quickly: from the physics and technology of how something works, to its implementation, the people involved, and the business case. I like to think I’m a clear and convincing communicator, with an eye for visual design and the bigger picture. I like taking the lead: setting a vision, explaining it clearly, and getting people behind it.
Core skills
Data science & ML
Python (NumPy, SciPy, pandas, scikit-learn, PyTorch, TensorFlow, matplotlib, Jupyter), Julia, R, SQL, MATLAB, C · Bayesian statistics, neural networks and deep learning, LLMs and generative AI, data visualisation
Signal processing
Time series analysis, filter design, Fourier/wavelet analysis, real-time detection, simulation
Spec-driven coding with agents (Claude Code, Claude in Chrome, GitHub Copilot), orchestrating multiple agents, and validating AI output
Experience
Freelance Software & Data Engineer— Ghent
Mar 2025 – present
Softwareshaker (NL), 2025 – 2026: full-stack developer on Workshaker, a work-order app for technicians, used by 400+ Dutch companies.
Translated the owner’s and customers’ requests into specs and shipped them to production; owned deploys and monitoring; made the ERP data sync up to 4× faster.
Built a WooCommerce (WordPress) → Robaws ERP integration, live at several customer webshops.
AI-native projects— Ghent · own initiative
2025 – present
Mic Archive: web app for audio professionals to compare recording microphones, plus research on mic setups for 114 musical instruments, with data from 681 sources, built by directing parallel AI coding and research agents.
Les Hémioles, a new folk music and social dancing festival (€50k+ budget; first edition May 2028).
Postdoctoral Researcher, Neuroinformatics— Ghent University
Apr 2024 – Dec 2024
Bayesian inverse modelling on large, multi-modal brain-imaging datasets, with Python pipelines; international collaboration in the European EBRAINS project.
Doctoral Researcher, Computational Neuroscience— University of Nottingham, UK
Feb 2020 – Jan 2024
Statistical and machine-learning methods to infer neural connectivity from voltage-imaging data (Python, Julia).
Built and performance-optimised a spiking neural network simulation library in Julia.
Shared knowledge: ~100 open research notebooks, Teaching Assistant at the COSYNE 2022 tutorial, a ‘Julia for Scientists’ talk (Julia is a programming language for science and data: as easy to write as Python, but as fast as C).
Research Engineer, Signal Processing— Neuro-Electronics Research Flanders (imec, VIB)
Apr 2019 – Jul 2019
Real-time detection of brain signals with spatiotemporal filtering and recurrent neural networks.
Internships
2016 – 2017
DataCamp (2016): production microservices and data pipeline · Byteflies (2017): motion-sensor data science for a medical wearable · Fluves (2017): business plan for an offshore-wind venture.