Hillol is a postdoctoral researcher at the Center of Healthcare Effectiveness Research. His research focuses on the analysis of physiological data from human subject studies in free-living condition. He had applied machine learning algorithms to infer location, stress, smoking, and user's availability from wearable sensor data. His research had revealed the statistically significant association between sensor inferred context (e.g., location) and adverse health outcomes (e.g., stress). His research is enabling the design of just-in-time mobile health (mHealth) intervention using wearable sensors to help users improve health and well-being.
Hillol received his MS and PhD in Computer Science from the University of Memphis. He was also affiliated with the Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K).