Mass casualty incidents (MCIs) are a growing concern. Recent efforts to improve the MCI emergency medical response focus on resource allocation, responder coordination, or transportation efficiency, and often overlook the initial, yet critical, step of tagging victims on scene. Tagging victims in minimal time is vital in providing information that guides subsequent time-constrained response actions. In this group we are designing practical algorithms to optimize the time it takes for medical responders to tag victims, while considering real-world constraints such as global vs. local communication.
Contact
If you feel like your skills and interests are aligned with this project, please reach out to Maria Cardei to get involved!Publications
News
Our paper Practical Heuristics for Victim Tagging During a Mass Casualty Incident Emergency Medical Response authored by PhD student Maria Cardei and Afsaneh Doryab, has been published in the 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE). Maria traveled to Bari, Italy to present our work!
Our abtract “Multi-Agent System for Optimizing Victim Tagging in Human/Autonomous Responder Teams” by PhD student Maria Cardei and Afsaneh Doryab, has been published in the 2024 ACM/IEEE 15th International Conference on Cyber-Physical Systems (ICCPS).