Projects

Selected work across healthcare AI, radar sensing, data engineering, and deployable machine learning systems.

Samsung HeartWise Healthcare App

Wearable healthcare platform work for remote cardiac rehabilitation, exercise tracking, BLE synchronization, and smartwatch-based patient engagement.

Prototype-based, interpretable machine learning for epileptic seizure prediction using biomedical time-series signals.

Multimodal skin disease classification combining dermoscopic images, clinical metadata, and explainability with Grad-CAM and SHAP.

End-to-end machine learning pipeline that predicts low, medium, or high patient risk from structured clinical data.

Machine learning pipeline for radar-based people counting in noisy real-world environments and constrained deployment settings.

CI/CD pipeline for machine learning projects with automated testing, deployment, and model versioning.

Python ETL project for world-bank-style data engineering workflows, covering extraction, transformation, and database loading.

Distributed data processing and machine learning pipeline using Apache Spark, Docker, and Python.

KNIME workflow for hypothesis testing on socio-economic, health, and service-access factors tied to development status and life expectancy.

PyTorch-based classification project for predicting League of Legends match outcomes from in-game statistics.

C++17 Sudoku solver that loads puzzles, verifies uniqueness, grades difficulty, and generates new puzzles with optional symmetry.

Machine learning models for employee attrition prediction, built to identify turnover risk and support retention decisions.

Exploratory data story on school-fire incidents in Sweden using visual analysis, geospatial patterns, and Power BI.