Dr. Ansari's research focuses on the development, validation and implementation of data science tools to address challenges in medicine and clinical care. Specifically, he applies signal processing, image processing and machine learning techniques, including deep convolutional and recurrent neural networks and natural language processing, to aid diagnosis, prognosis and treatment of patients with acute and chronic conditions. In addition, Dr. Ansari's research also focuses on the development of tools for maintenance and monitoring of machine learning models post-deployment. Another active area of his research is design, implementation and utilization of novel wearable devices for non-invasive patient monitoring in hospital and at home. This includes integration of the information that is measured by wearables with the data available in the electronic health records, including clinical data, waveforms and images, among others. Dr. Ansari's research also involves linear, non-linear and discrete optimization and queuing theory to build new solutions for healthcare organization, including stochastic approximation methods to model complex systems such as dispatch policies for emergency systems with multi-server dispatches, variable server load, multiple priority levels, etc.

Administrative Contact:
Denise Wieck
[email protected]

- Development and validation of AI/ML models for healthcare applications
- Deployment of clincal AI/ML models in electronic health records
- Development of clinical interventions for AI/ML models using human-centered design
- Post-deployment maintenance and monitoring of clinical AI/ML models
- Use of wearable devices for disease diagnosis and prognosis
- Use of optimization models to improve healthcare organization