OVERVIEW
- COVID-19 is a contagious respiratory disease that is known to spread rapidly through person-to- person contact.
- As organizations, cities, and municipalities reopen, they will need data on the adherence to physical distancing to inform programs and policies to stop the spread of COVID-19.
- Poirot collects information about individuals’ physical interactions in a privacy-preserving manner using secure multiparty computation and differential privacy to provide actionable information to decision-makers and the individuals themselves.
- To ensure privacy, Poirot only displays aggregate statistics collected about the contact events to decision-makers and this information cannot be linked back to any individual.
RESEARCH
BACKED BY GLOBAL HEALTH AND COMPUTER SCIENCE
TEAM
Our team consists of a group of researchers at Duke University from the Computer Science Department and the Department of Family Medicine and Community Health and Duke Global Health Institute. It is also advised by an expert panel in global health.
LEADERSHIP TEAM
Applied cryptography, Blockchains
Mobile systems and security
Privacy in statistical databases
Digital health intervention development and evaluation
Data-intensive systems and scalable data analytics
EXPERT COLLABORATORS
Infectious disease clinician and global health researcher
Pediatric infectious diseases clinician, epidemiologist, vaccinologist, and global health researcher
Health services researcher, epidemiologist, and global health researcher
Infectious disease clinician, epidemiologist, and global health researcher
POSTDOCS AND STUDENTS
Yanping
Zhang
Privacy and Security
Johes
Bater
Privacy and secure computation for databases
Chenghong
Wang
Privacy and applied cryptography
David
Pujol
Fairness in differential privacy
Vandan
Mehta
iOS Development,
Distance estimation
Haotian
Wang
iOS Development
Saloni
Bulchandani
Web Development
Jaidha
Rosenblatt
Web Development