Research Project: Racial Bias Detection
- Implemented several signal processing (e.g., data denoising, missing value imputation, and outlier detection) and feature extraction algorithms for physiological sensor signals, such as Heart Rate, PPG, EDA, and Skin Temperature.
- Built the XGBoost machine learning model to predict racial bias from physiological signals with 76.1% accuracy.