- Machine learning
- Computational health informatics
- Probabilistic Methods
- Time Series Models
- Information extraction in domains with structured and unstructured data (e.g., text, sensing devices, electronic health records, smart rooms)
- Predictive modeling in healthcare.
Saria’s interests span machine learning, its applications to domains such as natural language and time series data, and health informatics. She is particularly motivated by difficult and important problems that involve drawing inferences from large scale heterogeneous data sources such as electronic health records and sensing platforms (e.g., smart phones, kinects, body sensors). She earned her Ph.D. and her Masters in Computer Science from Stanford University in 2011 and her Bachelors in Physics and Computer Science from Mount Holyoke College. Prior to moving to Hopkins, she also spent a year as an NSF Computing Innovation fellow visiting the Intelligent Health Lab at Harvard University.
Secondary Appointments: Health Policy and Management, Bloomberg School of Public Health, Institute for Computational Medicine, Center of Population Health Information Technology, Center for Language and Speech Processing, Laboratory for Computational Sensing and Robotics, Armstrong Institute for Patient Safety & Quality.