The use of data gathered from smartphones and wearables is increasingly prevalent in identifying early indications of illnesses, allowing medical professionals to evaluate a patient’s well-being from a distance, or even better, automating the process. Nevertheless, accurately forecasting a patient’s emotional state using this data remains a formidable task. As part of my research, I integrate sensor and user interaction data to enhance the precision of predicting individuals’ stress levels.

This SuperUROP has given me a chance to do research at the intersection of machine learning and healthcare and to see how machine learning could change disease diagnostic process.