The MDAKM Laboratory participates in national and international research projects, funded by the European Commission, national and regional funding agencies, and private organizations. Below you can find information about our current and past projects.
Title: End-to-end Cybersecurity to NEMO meta-OS
Website: TBA
Description: Horizon project 101070118 ΝΕΜΟ (Next Generation Meta OS) builds an IoT-Edge-Cloud continuum, in the form of an open-source, flexible, adaptable, and multi-technology meta-Operating System. NEMO aims to unleash the power of Artificial Intelligence IoT to increase European autonomy in data processing and lower CO2 footprint. Leveraging on consortium partners technological excellence, along with clear business and exploitation strategies, CyberNEMO builds on top of NEMO to add end-to-end cybersecurity and trust on IoT-Edge-Cloud-Data Computing Continuum. CyberNEMO will establish itself as a paradigm-shift to support resilience, risk preparedness, awareness, detection and mitigation within Critical Infrastructures deployments and across supply chains. To achieve technology maturity and massive adoption, CyberNEMO will not “reinvent the wheel”, but leverage on existing by-design, by-innovation, and by-collaboration zero-trust cybersecurity and privacy protection systems, and introduce novel concepts, methods, tools, testing facilities and engagement campaigns to go beyond today’s state of the art and create sustainable innovation, already evident within the project lifetime. CyberNEMO will offer end-to-end and full stack protection, ranging from a low level Zero-Trust Network Access layer up to a human AI explainable Situation Perception, Comprehension & Protection (SPCP) framework and tools, collaborative micro-cervices Auditing, Certification & Accreditation and a pan-European Knowledge Sharing, risk Assessment, threat Analysis and incidents Mitigation (SAAM) collaborative platform. Validation and penetration testing will take place in 6 pilots including OneLab for integration, various Critical Infrastructures (Energy, Water, Healthcare), media distribution, agrifood and fintech supply chain, along with their cross-domain, cross-border federation. Sustainability and adoption will be offered via the de-facto European Open source Eclipse Foundation ecosystem.
Duration: 10/2024 – 9/2027
Role: Partner
Consortium: Synelixis Solutions S.A., Greece; DNV A.S., Norway; Thales Six GTS France S.A.S. TSG, France; Engineering – Ingegneria Informatica SPA, Italy; Netcompany – Intrasoft S.A., Luxemburg; SIEMENS SRL, Romania; Maggioli Group SPA, Italy; Space Hellas S.A., Greece; Cyber Ethics Lab, Italy; Digital Systems 4.0, Bulgaria; Unparallel Innovation LDA, Portugal; Telefonica Digital Espana, Spain Telecom Operator; Hellenic Telecom Organization S.A. (Deutsche Telecom Group) OTE Greece; ASM Terni SpA, Italy; Entersoft S.A., Greece; Medical University - Plovdiv Hospital, Bulgaria; Sorbonne Université, France; Universidad Politécnica De Madrid, Spain; Rheinisch-Westfälische Technische Hochschule Aachen, Germany; University of Patras, Greece; Charles III University of Madrid, Spain; Eclipse Foundation Europe GmbH, Germany; Open Source Ecosystem - Sphynx Technology Solutions AG, STS Switzerland Associated Partner
Funding: EUROPEAN COMMISSION, Directorate-General for Communications Networks, Content and Technology, DG/Agency: CNECT.H – Digital Society, Trust and Cybersecurity, H.1 – Cybersecurity Technology and Capacity Building, Project ID: 101168182 Programme: HORIZON Project: 101168182 — CyberNEMO — call: HORIZON-CL3-2023-CS-01
Total Budget: 5,999,747.00 €
Project Title: An innovative research project to unravel the special features of human breast milk and enrich formula milk using omics technologies
Website: http://darkdna.gr/milksafe/index.html
Description: We aim to perform an extensive comparative analysis of human breastmilk with three locally traded animal milks (domestic sheep, goats and cattle from different regions of Greece). In particular, a high-quality, quantitative and qualitative study will be conducted for the analysis of the membrane and intracellular composition of the major classes of secreted extracellular vesicles and other transported microparticles. The long term aim is to establish topological networks of phylogenetic distance across human biopolymers. The proposed multidimensional bioinformatics analysis will show which animal milk has the highest phylogenetic affinity for human milk based on specific nucleotide and amino acid sequences, and thus the highest nutritional value for neonates. Application of high-throughput techniques in combination with comparative genomic analysis of mRNAs, non-coding RNAs, proteins, and small molecules that bind or are encapsulated in secreted lipid membranes (exosomes) will be included.
Duration: 29/10/2020 – 30/9/2023
Role: Subcontractor
Consortium: Agricultural University of Athens (team from the Genetics Laboratory), Research University Institute of Maternal and Child Health, and Precision Medicine, ELGO Demeter, Gene Expression Laboratory, Molecular Diagnostics & Modern Therapeutic Means of the Democritus University of Thrace, GIOTIS S.A., EVROPHARM A.E., STAMOU A.E., and the Association of Greek Food Industries (SEVT)
Funding: Co-financed by the European Union’s European Regional Development Fund (ERDF) and national resources through the Operational Programme Competitiveness, Entrepreneurship, and Innovation (EPAnEK). Intervention II ‘Collaborations of Businesses with Research Organizations’ of the 2nd cycle of the Single Action for State Aid for Research, Technological Development & Innovation ‘RESEARCH – CREATE – INNOVATE.’ EPAnEK 2014-2020 Operational Programme Competitiveness, Entrepreneurship, Innovation.
Budget: 878,135.00 €
Project Title: Bridging big omical, genetic and medical data for the wide application of Precision Medicine in Greece
Website: http://gomedprecision.gr/
Description: The main objective of the project is the utilization of modern high-resolution molecular data (genetics, metabolomics, etc.) in order to integrate them (consolidation) in patient registries, so that in combination with clinical and epidemiological data they can contribute to an integrated environment of an innovative Smart-Electronic Health Record (E-EFY) with embedded clinical decision/prediction support subsystems for the support of physicians and personalized therapeutic approaches. By employing state-of-the-art technologies for the management of large-scale data and the development of new algorithmic methods, the project focuses on improving disease prognosis and clinical management, through understanding the genetic background of each individual patient, so as to determine the risk of developing both rare and common diseases such as cardiovascular diseases, metabolic disorders, and various cancers.
Duration: 8/2023 – 12/2025
Role: Development of Machine Learning Models for Knowledge Mining and Patient Categorization
Consortium: University of Thessaly, Biomedical Sciences Research Center “A. Fleming”, University of Patras, Hellenic Pasteur Institute
Funding: General Secretariat for Research and Technology
Budget: €2,392,436
Budget Work Package: €165,921
Project Title: Sensing and predictive treatment of frailty and associated co-morbidities using advanced personalized models and advanced interventions
Website: http://frailsafe-project.eu
Description: Ageing population is steeply increasing worldwide. A consequence of age related decline is the clinical condition of frailty. Frailty is a biological syndrome of decreased reserve and resistance to stressors, resulting from cumulative declines across multiple physiologic systems and causing vulnerability to adverse outcomes. Susceptibility to stressors is influenced by biological, behavioral, environmental, and social risk factors, with the main consequence being an increased risk for multiple adverse health outcomes, including disability, morbidity, falls, hospitalization, institutionalization, and death. However, frailty is a dynamic and not an irreversible process; it seems preventable, may be delayed, or reversed. Our understanding of frailty has markedly improved over the last five years, yet there are many issues yet to be resolved. FrailSafe aims to better understand frailty and its relation to co-morbidities; to identify quantitative and qualitative measures of frailty through advanced data mining approaches on multiparametric data and use them to predict short and long-term outcome and risk of frailty; to develop real life sensing (physical, cognitive, psychological, social) and intervention (guidelines, real-time feedback, Augmented Reality serious games) platform offering physiological reserve and external challenges; to provide a digital patient model of frailty sensitive to several dynamic parameters, including physiological, behavioural and contextual; this model being the key for developing and testing pharmaceutical and non-pharmaceutical interventions; to create “prevent-frailty” evidence-based recommendations for the elderly; to strengthen the motor, cognitive, and other “anti-frailty” activities through the delivery of personalised treatment programmes, monitoring alerts, guidance and education; and to achieve all with a safe, unobtrusive and acceptable system for the ageing population while reducing the cost of health care systems.
Duration: 01/2016 – 06/2019
Role: Coordinator
Consortium: University of Patras (Greece), Brainstorm Multimedia (Spain), Smartex (Italy), AGE Platform Europe (Belgium), Center for Research and Technology Hellas/Information Technologies Institute (Greece), Materia Group (Cyprus), Gruppo SIGLA (Italy), Hypertech (Greece), University Hospital of Nancy and INSERM U1116 Nancy (France)
Funding: H2020-PHC-21-2015
Budget: 3,820,896.25 €