About
I'm an AI/ML Engineer and Data Scientist based in Oslo, currently completing an MSc in Artificial Intelligence at Kristiania University College. I build machine learning systems focused on explainability — making AI decisions understandable and trustworthy. My work spans anomaly detection, predictive modelling, time-series forecasting, and computer vision. I publish my projects at K|Intel Analytics.
What I've Built
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Unsupervised segmentation of 678,013 French auto insurance policies using K-Means and PCA to surface three actuarially distinct risk profiles — validated with Kruskal-Wallis.
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Four studies across data mining and computer vision: network graph mining on movie data, NLP classification on farm advertisements, low-light image enhancement, and AR landmark recognition.
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PySpark pipeline over 2020–2024 NYC Yellow and Green Taxi trip records — Parquet ingest, Spark SQL cleaning, feature engineering, and a Spark ML regression to predict fare amount. Companion Gradio app replays the EDA queries against persisted SQLite samples.
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End-to-end supervised ML pipeline for heart disease prediction — preprocessing, logistic regression, random forest, 5-fold cross-validation, and unsupervised pattern discovery.
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Deep learning pipeline (1D CNN, LSTM, and a CNN-LSTM hybrid) to predict forward realized volatility of SPY over 5- and 10-day horizons using 30 years of price history.
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Hybrid anomaly and signature-based IDS on the CIC-IDS-2017 dataset, with SHAP and LIME to make model decisions interpretable for security analysts.
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Logistic-regression churn model on a 10 000-row European retail-banking dataset, wrapped in a live what-if calculator — pick a real customer, nudge their attributes, watch the prediction and driver breakdown update in real time.
Selected Builds
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A full-stack marketing and booking website for a California hair studio, live in production. Built with Next.js, Supabase, and Tailwind and deployed on Netlify — with a services and pricing system driven from a single source of truth, an image gallery, email signup, and an integrated booking handoff.
Experiments
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A Norwegian language-learning tool built through iterative LLM collaboration: type any word or phrase and get a full linguistic entry — translation, IPA, all inflected forms, examples, grammar notes, and slang detection — then save what you're weak at and track high-frequency-word progress.