LONDON * ZURICH * EUROPE-WIDE
AI Software Engineer & Data Scientist
I specialise in deciphering complex data and transforming it into actionable, profitable knowledge. My approach is rooted in astrophysics, where I mastered the art of extracting signal from noise in sophisticated datasets– a rigor I now apply to AI-driven biotech and precision engineering.
Current Impact: AI in Biotech
- Architected scalable Python pipelines for rare cell detection in high-throughput imaging
- Optimised Deep Learning models (Tensorflow) to increase signal-from-noise ratio in microscopic datasets
- Bridging the gap between R&D research and production-ready software for clinical diagnostics
Applying Expertise Across Domains
Smart Cities & IoT
Applying spatial data analysis and time-series forecasting to urban mobility and infrastructure optimisation
Smart Farming & Sustainability
Leveraging satellite imagery and computer vision--honed in observational cosmology--for precision agriculture
Public Policy & Social Science
Using Bayesian statistics and evidence-based modelling to inform complex decision-making and policy impact
Scientific Roots
A decade of PhD/PostDoc research in Cosmology provided a foundation in extreme-scale data modelling and statistical rigour.
CORE TECHNICAL STACK
LANGUAGES: Python | C | Fortran | SQL | R AI/ML: Keras | Tensorflow | PyTorch | Computer Vision | Scikit-Learn | Bayesian Inference OPS: Docker | Git | Linux | GCP/AWS Speciality: Geospatial Data | Time-Series Analysis