Message from IEEE Greece Section on COVID-19

Dear colleagues – members of the IEEE Greece section,

I hope that you and your beloved ones are doing well amidst this unprecedented global health crisis.

IEEE is closely monitoring the updates concerning the coronavirus (COVID-19) outbreak and would like to shine a light on its very own IEEE members who are on the “front line”, developing tools and technologies to address this pandemic, and future ones. 

If you would like to share such news with us, please email us back at a short description of the activities you are involved in, so that we can contribute in IEEE’s effort towards collecting such information and creating a relevant “central repository” which IEEE members will be able to access via the Institute’s website. 

Take care. Stay safe.

Konstantina Nikita, IEEE Greece Section Chair

Organisations with activities against the COVID-19 pandemic:

School of Electrical and Computer Engineering – National Technical University of Athens

Intelligent Data Exploration and Analysis Laboratory (IDEAL) – University of the Aegean

BEYOND Center of Excellence

School of Electrical and Computer Engineering – National Technical University of Athens

The School of Electrical and Computer Engineering at the National Technical University of Athens, paves the way for developing new projects which aim at assisting in the fight against COVID-19 outbreak.

Advanced Data Science and Data Analytics Course

The postgraduate ECE course “Advanced Data Science and Data Analytics” (CS708) tackles current challenges in processing and learning from big data. The course started in the academic year 2015 – 2016. You can find its regular syllabus at its official school page. For the current academic year, exceptionally, the course takes the form of a project class and focuses exclusively on Data Analytics / Data Science tasks related to the COVID-19 pandemic.


Potential research areas include:

  • Natural Language Processing
  • Social Networks
  • Bioinformatics
  • Epidemiological Data Analysis
  • Computer Vision
  • Financial Implications
  • Other (TBD)


For all course and project-related questions, please mail to

  • Georgios Alexandridis, TRA (gealexandri at islab ntua gr)
  • Georgios Siolas, TRA (gsiolas at islab ntua gr)
  • Paraskevi Tzouveli, TRA (tpar at image ntua gr)


The teaching staff created a website initially as a data repository for the course. At the same time, numerous other AILS research teams are pursuing COVID-19 projects. Therefore, the site aims to become a hub for publishing results and news of all AILS activity regarding COVID-19.

Website URL:
Twitter: @AILS_Covid19

m-health and e-health Technologies Course

The undergraduate ECE course “m-health and e-health Technologies” (3.2.3382.8) focuses on innovative and disruptive technologies and applications in health. The course started in the academic year 2016 – 2017. You can find its regular syllabus on its official school page. The course applies project-based learning in order to provide students the opportunity to gain hands-on experience in academic research, design and development theories and methodologies for healthcare solutions. This academic year, many of the student projects are related to AI technologies addressing COVID-19 pandemic challenges.


The following COVID-19 related projects supported by the Biomedical Simulations and Imaging (BioSim) Lab are underway:

  • AI techniques to investigate the spread of COVID-19 based on epidemiological, demographic, healthcare policy and geospatial data.
  • Design and development of a smart mobile app for detecting fatigue in healthcare professionals.
  • Design and development of a Chatbot for physical activity recommendations to quarantined population, based on emotion detection through AI techniques.
  • Design and development of a Serious Game for the empowerment of isolated people suffering from depression.


For all course and above project-related questions, please contact:
• Kostas Mitsis (Teaching Assistant,

Intelligent Data Exploration and Analysis Laboratory – University of the Aegean

The Intelligent Data Exploration and Analysis Laboratory (IDEAL) of the University of the Aegean has utilized its expertise on the areas of machine learning, data mining and natural language processing in order to develop tools that address a list of initial key scientific questions that are drawn from the NASEM’s SCIED (National Academies of Sciences, Engineering, and Medicine’s Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats) research topics and the World Health Organization’s R&D Blueprint for COVID-19 using the COVID-19 Open Research Dataset (CORD-19), which is  a resource of over 44,000 scholarly articles, including over 29,000 with full text, about COVID-19, SARS-CoV-2, and related coronaviruses. The questions addressed include:

  1. What is known about transmission, incubation, and environmental stability?
  2. What do we know about COVID-19 risk factors?
  3. What do we know about virus genetics, origin, and evolution?
  4. What do we know about vaccines and therapeutics?
  5. What do we know about non-pharmaceutical interventions?
  6. What do we know about diagnostics and surveillance?
  7. What has been published about medical care?
  8. What has been published about ethical and social science considerations?
  9. What has been published about information sharing and inter-sectoral collaboration?

BEYOND Center of Excellence

The BEYOND Center of Excellence, which develops research and provides disaster management services addressing priorities and needs in South Eastern Europe, Mediterranean, N. Africa, Middle East and the Balkans, published the new edition of WEB GIS COVID-19 platform for continuous monitoring of COVID-19 global spread. The data analysed by the platform are collected from four independent sources: (i) European Centre for Disease Prevention and Control (ECDC), (ii) John Hopkins University, (iii) World Health Organisation (WHO), and (iv) trustworthy news agencies. Plots regarding confirmed cases by country, deaths by country, country participation rate to the number of cases worldwide, and death rate by country are updated daily for nine countries (China, USA, Greece, Italy, France, Spain, Switzerland, UK and Germany). Such analysis may help decoding possible relations among social, economic, geographic and natural environment parameters and the pandemic.