Dr. Ebadi’s research concerns applied data science, with a special focus on medical informatics, and covers: 1) development of scalable and intelligent decision support systems, 2) hybrid recommender systems, and 3) hyper graphs analytics and evolution. He has successfully applied such techniques in large-scale real world health applications based on machine learning and deep learning methods. He has also a well-established track of collaboration with other researchers at both national and international levels, and produced several peer-reviewed publications from these collaborative projects.

Research Projects

1. AI-enabled radiography diagnostics

2. Intelligent decision support systems for research evaluation

3. Gender disparity in science

4. Expert recommender systems

5. Collaboration patterns in complex networks