Novel Methods to Study COVID-19 Using Sensor Technology and Distributed Computing 2023
Coral Bay, Pafos, Cyprus
June 19-21, 2023
Co-located with DCOSS 2023
Click here for submission link
Scope
This workshop will cover a number of aspects related to the COVID-19 pandemic. Topics of interest for C19:ST&DC include several novel methods used for COVID-19 detection using deep learning and distributed computing methods. Distributed computing has accelerated COVID-19 research in molecular dynamics as it allows people around the world to make their computers available to researchers for effective virtual screening of chemical compounds. Distributed computing encourages international collaboration and enables access to richer datasets.
Topics of Interest
- Innovative machine learning and artificial intelligence techniques applied to chest CT and x-ray images to identify features of interest in COVID-19 patients, improve accuracy of diagnosis, identify illness severity, and study the spread and long-term effects
- Wireless, non-invasive sensors for COVID-19 detection, including sensor technology that can detect COVID-19 infections, low-cost and portable devices for remote patient monitoring and virtual assessments, and other types of sensors for monitoring COVID-19
- Innovative methods for improving accuracy, fast response time, multiplexing capabilities, multiple sensing modes, disposability, long shelf life, ease of use, cost-effectiveness, manufacturability, and autonomy
- Legal, ethical, and privacy concerns surrounding sensor technology and associated data
- Methods from nanotechnology and the Internet of things, as they are applicable to COVID-19 sensor technology
- Informatics and standardization techniques for archiving multimodal data related to COVID-19
- The need for large amounts of data for the relevant types of machine learning methods
- Various metrics of quality control of imaging data
- Web-based interactive data visualization platforms, user interfaces and graphical tools for integrated data processing to explore data, and access pipeline workflows
- Distributed computing applied to COVID-19 for various types of data
- Various types of distributed architectures, including clusters, grids, and clouds, that are being used to accelerate COVID-19 research
Chairs
- Dominique Duncan, University of Southern California
- Celina Alba, University of Southern California
10 papers, 2 keynotes (other papers will be shorter talks), selection of papers via both invitation and open call
Important Dates
- Abstract Submission: January 30, 2023
- Paper Submission: February 6, 2023
- Acceptance Notification: April 7, 2023
- Camera Ready: April 28, 2023
- Early Registration: TBA
- Workshop Day: TBA
Publicity via the COVID-19 Data Archive (COVID-ARC) website.