I'm a data scientist and ML engineer based in Warsaw. I mainly work on causal inference, NLP, and computer vision. I like projects where the evaluation & result is as important as the model.
I graduated from the MSc in Data Science & Business Analysis at the University of Warsaw in 2026, after completing a BSc in Neuroinformatics. Besides side projects & work I am also part of the NeuroInformatics science club, if you want to join, help organize and event or participate in one - please reach out!:)
- Causal ML for crypto-market manipulation: the public companion to my master's thesis. I studied 12.4M Telegram messages and tested the predictive model on channels it had never seen. The thesis reported macro-F1 0.76 and recall 0.89 for successful events. The public repository uses synthetic data.
- Agentic API readiness: a Python tool for checking how an OpenAPI specification behaves when an agent uses the API through MCP. It validates the spec, runs test workflows, grades traces, and removes sensitive values from reports.
- EuroSAT RGB classification: a ResNet18 classifier for ten land-use classes, with a fixed data split and three preprocessing variants. The original project run reported 89.53% test accuracy.
- Reddit supplement NLP: a streaming text-analysis tool for finding supplement mentions, questions, sentiment, negation, and aspects in Reddit discussions.
- StressAware HRV: a course project with Paula Banach that combines an R/Shiny app with Python HRV preprocessing and WESAD-based stress experiments.
- Main interests: causal inference, NLP, computer vision, biosignals, evaluation
- Languages: Python, R, SQL
- Selected tools: PyTorch, scikit-learn, Transformers, XGBoost, EconML, Docker, GitHub Actions