- MEDINFO23We are thrilled to announce that our research paper, “Pandemic Management – Health Data and Public Health Surveillance,” has been accepted as a poster presentation at the upcoming MedInfo 2023 conference, which will be held in Sydney, Australia, in July!
- INFORMS Annual ConferenceMOSAIC LAB Presents at The INFORMS Annual Meeting in Indianapolis. As INFORMS brings together over 6,000 people to the world’s largest Operations Research and Analytics conference, our work entitled “The Role of Digital Health Technology in Neurological Disease Staging” provided both interest and detailed discussion on the current state of healthcare while providing a vision for future research and applications in this arena.
- Cyber Florida GrantThe State of Florida has awarded multiple FIU schools more than $2 million to fund projects focused on educating and preparing students for careers in cybersecurity and information technology, including a project spearheaded by the MOSAIC Lab. These grants, funded by the Cybersecurity and Information Technology Pathways program, will help grow FIU-led programs meant to address the national skills shortage in cybersecurity and information technology […]
The MOSAIC (Mobile Sensing and Analytics) Lab at Florida International University (FIU) investigates how mobile, wireless, and wearable computers and sensors can be used to address many pressing problems in areas such as healthcare, conservation, transportation, education, and more. Our lab studies a variety of sensing challenges, such as how to design participatory and opportunistic data collections at large scales and over long period of times, how to fuse many different sensing modalities, how to use context information to increase the sensing efficiency and the quality of the collected data, and how to do all that in a secure and privacy-conserving manner. From an analytics perspective, we use the collected data to obtain insights into user behavior and to provide opportunities for the early detection of various diseases and to monitor disease progression or patient recovery. We also investigate how to use the insights obtained from the sensor data to to develop new solutions in areas such as smart cities, smart transportation, and wireless communications. Our work also investigates how to develop machine and deep learning techniques that can provide timely decisions and outputs on resource-constrained and distributed systems.