I’m a Data Scientist with a background in systems development, specializing in Artificial Intelligence (AI) and Machine Learning (ML). I build production-ready AI systems that are secure, privacy-preserving, and designed for real-world impact across multiple industries. I’ve worked with public-sector authorities on GDPR-compliant AI, privacy-preserving techniques, and secure handling of sensitive data, combining hands-on engineering with regulatory and risk awareness.
A core part of my work is failure-mode thinking: understanding how AI systems break through data leakage, weak access controls, insecure integrations, or poorly governed pipelines, and designing architectures that reduce those risks.
- Digit Recognition
A Streamlit web application for recognizing handwritten digits (0-9) using a Convolutional Neural Network (CNN) trained on the MNIST dataset.
Features:
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Draw Mode: Draw a digit directly on the canvas.
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Upload Mode: Upload an image of a handwritten digit.
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Real-time Prediction: See prediction results instantly.
Try it out →
- Digiti Signum
An scientific research project demonstrating fingerprint matching and alteration detection using both traditional computer vision and deep learning approaches. This project explores how biometric systems work behind the scenes to match fingerprints and detect alterations.
Features:
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SIFT feature extraction - Identifying distinctive points in fingerprint images
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Custom 5-layer CNN - Training a CNN from scratch for fingerprint classification
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Transfer Learning with ResNet18 - Leveraging pre-trained ImageNet features
- Atlas
Atlas — Web-scraping toolkit for Swedish authorities. Automates data collection with pagination, PDF crawling, metadata extraction, and multi-format export.
Features:
- Browser Automation - Handles JavaScript-rendered pages and cookie consent dialogs using Playwright
- Pagination Support - Automatically navigates multi-page listings and "load more" buttons
- PDF Crawler - Recursively finds and downloads PDF documents with section-based organization
- Metadata Extraction - Captures document IDs (Serienummer, Diarienummer), dates, titles, and descriptions
- Project Jackheart
Project Jackheart is an educational project demonstrating byte-level file techniques: hiding data in JPEGs, embedding images inside images, building polyglot files, and header-level codec-aware MP3 steganography (private-bit embedding + AES-GCM). The notebooks emphasize secure, local experimentation, reproducibility, and OPSEC.
Features:
- How file formats are structured
- How parsers interpret binary data
- How steganography differs from polyglots
- Why “file extensions” do not define file behavior
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Project Foresight
Try it out →
Note: since this is a WIP, it may not be accessible at all times.
Predicts weather temperature using machine learning and automated workflows.
Features:
- Integrates real-time weather and traffic data.
- Outputs weather temperature predictions based on real-time data.
- Automates data ingestion, processing, and ML predictions.
- 🌱 Currently deepening my knowledge in cybersecurity and open to roles in this space
- 👯 Open to collaborating on AI and cybersecurity projects — discussions and joint work welcome
