Portfolio

Current focus

As a Senior AI/ML Architect at Aeven, my current areas of expertise span:

• IT infrastructure and AI sovereignty: understanding control over data, infrastructure, and model dependencies in AI architecture.
• AI-assisted coding: applying coding assistants with attention to review, validation, and software quality.
• Observability, DevOps, and Kubernetes: hands-on experience with monitoring, delivery, infrastructure operations, and the surrounding open-source tools.
• AI agents: understanding tool use, workflow orchestration, and evaluation of agent behavior.
• Foundation models and evaluation: following models for time-series forecasting, anomaly detection, and tabular prediction, including comparative resources such as the TabArena leaderboard.

Selected work

• Medical Artificial Intelligence Toolbox (MAIT): Open-source Python framework for ML workflows, model interpretability, and reproducibility.
• ExplaineR CRAN package: R package leveraging SHAP for explainable AI.
• Datasheets for AI and Medical Datasets (DAIMS): Data validation and documentation framework for medical research.
• ML-powered biofeedback system for personalized fatigue reduction.
• NLP-integrated survey platform for sentiment analysis.
• Development of ML models for international cohort studies in precision medicine.
• End-to-end AI solutions for insurance claim handling.
• Agile project management and reproducible research using Docker, GIT, and HPC clusters.