AI/ML project classifying Parkinson's-related tremors from wearable sensor data using Random Forest, XGBoost, CNN, and LSTM models.
Selected for MIT's competitive Beaver Works Summer Institute, a rigorous project-based STEM program.
Tested machine-learning models to classify Parkinson's-related tremor patterns from wearable sensor data.
Explored whether tremor patterns could help distinguish Parkinson's from other neurodegenerative disorders.
Evaluated Random Forest, Logistic Regression, XGBoost, CNN, and LSTM models, analyzing tremor frequency and model performance.