Data Science, Machine Learning & Computer Vision

Production-ready models and dashboards that turn images and data into decisions.

Images and data contain answers that are hard to get at by hand: cell structures in microscopy, defects on a production line, trends in quality data.

I develop computer vision models and data science solutions from research to production, including when labelled data is scarce. My research in self-supervised medical image segmentation is published on arXiv.

Typical use cases

Medical image analysis

Segmentation of cells, tissue and structures in 2D and 3D images.

Visual quality control

Detecting defects and anomalies in production images.

Dashboards & KPIs

Interactive dashboards and automated reporting from your data.

Forecasts & scenarios

Predictive models and digital twins for planning decisions.

Related case study

Medical AI · Research

Self-Supervised 3D Cancer Cell Segmentation

Challenge
A medtech company needed to segment cancer cells in very large 3D light-sheet microscopy scans, where expert annotations are slow and expensive.
Result
Segmentation 3% better than expert-annotated masks and 20% higher downstream diagnostic accuracy. Published on arXiv and under review at Pattern Recognition (Elsevier).
  • PyTorch
  • Swin Transformer
  • Self-Supervised Learning
  • Azure ML
Read case study →
Data Science · Modelling

Digital Twin for Population, Traffic & Energy

Challenge
Planners needed to understand how population growth and migration would affect traffic, energy use and CO₂ emissions across Bosnia and Herzegovina.
Result
CO₂-reduction and cost-optimisation scenarios for Sarajevo, based on one consistent, data-driven model.
  • Python
  • GIS
  • Scenario Modelling
  • Energy Systems
Read case study →

Ways to Start

Small first steps, clear results

Half day · fixed price
AI Opportunity Workshop

We map your processes, identify the 2–3 AI use cases with the best return, and leave you with a prioritised roadmap.

4 weeks · fixed scope
AI Pilot: Agent, RAG or ML

A working prototype on your own data, tested with real users before you invest further.

1–2 days · fixed price
AI & Data Readiness Check

A review of your data, tools and privacy requirements (GDPR, nDSG), with clear recommendations on which AI approach fits: cloud, hybrid or on-premise.

How I Work

From idea to production in four steps

  1. Discover

    A free 30-minute call, then a workshop to understand your processes, data and privacy requirements.

  2. Pilot

    A small, fixed-scope prototype on your real data, so you see the value before investing further.

  3. Deploy

    Production rollout in your cloud or on your own infrastructure, integrated with the tools your team already uses.

  4. Support

    Monitoring, model updates, training for your team and continuous improvement.

Other services

Let’s find out what AI can do for you

A free, no-obligation 30-minute call. You describe your processes or data, and I show you where AI could help and what a sensible first step looks like.

Book a free 30-min consultation →