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Request date Sort ascending	Organisation name	Country	Search type	Topic	Link
09/04/2023	DIGI Mind Sphere	Italy	Expertise Request	SNS Societal Challenges (HORIZON-JU-SNS-2023-STREAM-CSA-01)	F&T portal
The 4 main projects: Artificial Intelligence Big data Cyber security Ethical solutions and moral frameworks in the process of creation of AI Artificial intelligence development: ➢ Design of agents ➢ Development of training frameworks for agents ➢ Development ML models Design and development of data pipelines: ➢ Unique design of a data eco-systems ➢ Design and implementation of high-quality data pipelines ➢ Application of bias filters Contact: [email protected]
09/04/2023	BEIA CONSULT INTERNATIONAL SRL	Romania	Expertise Request	Pan-European network for Advanced Packaging made in Europe (CSA) (HORIZON-KDT-JU-2023-3-CSA-TOPIC-2)	F&T portal
R&D performing SME founded in 1991, leading ICT integrator in Romania with offices in Austria and Belgium. BEIA is ISO certified with experience in coordinating & participating in over 60 R&D Innovation projects (FP6, FP7, Horizon, Eureka, ERA-Net, etc.) on cloud, IoT, AI, 5G, blockchain/quantum/security (3DSafeGuard, 5G-SAFE+, ALADIN, Arrowhead, HUBCAP, S4ALLCITIES, SealedGRID, SWITCH, SOLID-B5G, SARWS, FOR-FREIGHT, FLEXI-CROSS, EV-BAT, UPSIM, VITAL-5G, etc.): [email protected] / www.beia.eu
09/04/2023	DIGI Mind Sphere	Italy	Expertise Request	System Architecture (HORIZON-JU-SNS-2023-STREAM-B-01-01)	F&T portal
The 4 main projects: Artificial Intelligence Big data Cyber security Ethical solutions and moral frameworks in the process of creation of AI Artificial intelligence development: ➢ Design of agents ➢ Development of training frameworks for agents ➢ Development ML models Design and development of data pipelines: ➢ Unique design of a data eco-systems ➢ Design and implementation of high-quality data pipelines ➢ Application of bias filters Contact: [email protected]
09/04/2023	ASOCIATIA BEIA - GRID INSTITUT	Romania	Expertise Request	Improving the global demand supply forecast of the semiconductor supply chain (IA) (HORIZON-KDT-JU-2023-3-IA-TOPIC-1)	F&T portal
R&D performing SME founded in 1991, leading ICT integrator in Romania with offices in Austria and Belgium. BEIA is ISO certified with experience in coordinating & participating in over 60 R&D Innovation projects (FP6, FP7, Horizon, Eureka, ERA-Net, etc.) on cloud, IoT, AI, 5G, blockchain/quantum/security (3DSafeGuard, 5G-SAFE+, ALADIN, Arrowhead, HUBCAP, S4ALLCITIES, SealedGRID, SWITCH, SOLID-B5G, SARWS, FOR-FREIGHT, FLEXI-CROSS, EV-BAT, UPSIM, VITAL-5G, etc.): [email protected] / www.beia.eu
07/04/2023	SD Companies SRL	Italy	Expertise Request	Call on Centres Of Excellence For Exascale HPC Applications (HORIZON-EUROHPC-JU-2023-COE-01-01)	F&T portal
SD Companies srl is a company specialized in Research and Development activities, i.e. from the conception of technological products to prototyping, integrating software, mechanical parts, electronic PCB, hardware and mechatronics systems. Our team of engineers, physicists and manufacturer experts are able to help clients in developing the project of whatever type facing all type of technical challenges, supporting R&D teams in what they lack in terms of knowledge or supplying custom components
07/04/2023	MINDS & SPARKS GMBH	Austria	Expertise Request	Coordination of the European software-defined vehicle platform (CSA) (HORIZON-KDT-JU-2023-3-CSA-TOPIC-3)	F&T portal
M&S is an experienced project partner with a skilled team of researchers, engineers, developers and creatives offering APPLIED RESEARCH: Stakeholder Analysis, User Surveys, Requirements Engineering. DEVELOPMENT: Conception, Web Applications, Interface Design, Data Visualization, Piloting, Validation. DISSEMINATION & EXPLOITATION: Websites, Communication, Innovation and Technology Marketing, Solution Assessments, Market Analysis, Exploitation Planning. OUR PROFILE: http://bit.ly/mindsandsparks
07/04/2023	BEIA CONSULT INTERNATIONAL SRL	Romania	Expertise Request	Global call according to SRIA 2023 (RIA) (HORIZON-KDT-JU-2023-2-RIA-TOPIC-1)	F&T portal
R&D performing SME founded in 1991, leading ICT integrator in Romania with offices in Austria and Belgium. BEIA is ISO certified with experience in coordinating & participating in over 60 R&D Innovation projects (FP6, FP7, Horizon, Eureka, ERA-Net, etc.) on cloud, IoT, AI, 5G, blockchain/quantum/security (3DSafeGuard, 5G-SAFE+, ALADIN, Arrowhead, HUBCAP, MULTI-AI, SAFECARE, S4ALLCITIES, STAMINA, SealedGRID, SWITCH, SOLID-B5G, SARWS, TESTBED2, UPSIM, VITAL-5G, etc.): [email protected] / www.beia.eu
07/04/2023	SD Companies SRL	Italy	Expertise Request	Coordination of the European software-defined vehicle platform (CSA) (HORIZON-KDT-JU-2023-3-CSA-TOPIC-3)	F&T portal
SD Companies srl is a company specialized in Research and Development activities, i.e. from the conception of technological products to prototyping, integrating software, mechanical parts, electronic PCB, hardware and mechatronics systems. Our team of engineers, physicists and manufacturer experts are able to help clients in developing the project of whatever type facing all type of technical challenges, supporting R&D teams in what they lack in terms of knowledge or supplying custom components
07/04/2023	MINDS & SPARKS GMBH	Austria	Expertise Request	Wireless Communication Technologies and Signal Processing (HORIZON-JU-SNS-2023-STREAM-B-01-02)	F&T portal
M&S is an experienced project partner with a skilled team of researchers, engineers, developers and creatives offering APPLIED RESEARCH: Stakeholder Analysis, User Surveys, Requirements Engineering. DEVELOPMENT: Conception, Web Applications, Interface Design, Data Visualization, Piloting, Validation. DISSEMINATION & EXPLOITATION: Websites, Communication, Innovation and Technology Marketing, Solution Assessments, Market Analysis, Exploitation Planning. OUR PROFILE: http://bit.ly/mindsandsparks
07/04/2023	SD Companies SRL	Italy	Expertise Request	Focus Topic on Hardware abstraction layer for a European Vehicle Operating System (RIA) (HORIZON-KDT-JU-2023-2-RIA-FOCUS-TOPIC-2)	F&T portal
SD Companies srl is a company specialized in Research and Development activities, i.e. from the conception of technological products to prototyping, integrating software, mechanical parts, electronic PCB, hardware and mechatronics systems. Our team of engineers, physicists and manufacturer experts are able to help clients in developing the project of whatever type facing all type of technical challenges, supporting R&D teams in what they lack in terms of knowledge or supplying custom components
07/04/2023	MINDS & SPARKS GMBH	Austria	Expertise Request	Call on Centres Of Excellence For Exascale HPC Applications (HORIZON-EUROHPC-JU-2023-COE-01-01)	F&T portal
M&S is an experienced project partner with a skilled team of researchers, engineers, developers and creatives offering APPLIED RESEARCH: Stakeholder Analysis, User Surveys, Requirements Engineering. DEVELOPMENT: Conception, Web Applications, Interface Design, Data Visualization, Piloting, Validation. DISSEMINATION & EXPLOITATION: Websites, Communication, Innovation and Technology Marketing, Solution Assessments, Market Analysis, Exploitation Planning. OUR PROFILE: http://bit.ly/mindsandsparks
07/04/2023	BEIA CONSULT INTERNATIONAL SRL	Romania	Expertise Request	Coordination of the European software-defined vehicle platform (CSA) (HORIZON-KDT-JU-2023-3-CSA-TOPIC-3)	F&T portal
R&D performing SME founded in 1991, leading ICT integrator in Romania with offices in Austria and Belgium. BEIA is ISO certified with experience in coordinating & participating in over 60 R&D Innovation projects (FP6, FP7, Horizon, Eureka, ERA-Net, etc.) on cloud, IoT, AI, 5G, blockchain/quantum/security (3DSafeGuard, 5G-SAFE+, ALADIN, Arrowhead, HUBCAP, S4ALLCITIES, SealedGRID, SWITCH, SOLID-B5G, SARWS, FOR-FREIGHT, FLEXI-CROSS, EV-BAT, UPSIM, VITAL-5G, etc.): [email protected] / www.beia.eu
07/04/2023	SD Companies SRL	Italy	Expertise Request	Global call according to SRIA 2023 (RIA) (HORIZON-KDT-JU-2023-2-RIA-TOPIC-1)	F&T portal
SD Companies srl is a company specialized in Research and Development activities, i.e. from the conception of technological products to prototyping, integrating software, mechanical parts, electronic PCB, hardware and mechatronics systems. Our team of engineers, physicists and manufacturer experts are able to help clients in developing the project of whatever type facing all type of technical challenges, supporting R&D teams in what they lack in terms of knowledge or supplying custom components
07/04/2023	SD Companies SRL	Italy	Expertise Request	Pan-European network for Advanced Packaging made in Europe (CSA) (HORIZON-KDT-JU-2023-3-CSA-TOPIC-2)	F&T portal
SD Companies srl is a company specialized in Research and Development activities, i.e. from the conception of technological products to prototyping, integrating software, mechanical parts, electronic PCB, hardware and mechatronics systems. Our team of engineers, physicists and manufacturer experts are able to help clients in developing the project of whatever type facing all type of technical challenges, supporting R&D teams in what they lack in terms of knowledge or supplying custom components
07/04/2023	BEIA CONSULT INTERNATIONAL SRL	Romania	Expertise Request	Focus Topic on Hardware abstraction layer for a European Vehicle Operating System (RIA) (HORIZON-KDT-JU-2023-2-RIA-FOCUS-TOPIC-2)	F&T portal
R&D performing SME founded in 1991, leading ICT integrator in Romania with offices in Austria and Belgium. BEIA is ISO certified with experience in coordinating & participating in over 60 R&D Innovation projects (FP6, FP7, Horizon, Eureka, ERA-Net, etc.) on cloud, IoT, AI, 5G, blockchain/quantum/security (3DSafeGuard, 5G-SAFE+, ALADIN, Arrowhead, HUBCAP, S4ALLCITIES, SealedGRID, SWITCH, SOLID-B5G, SARWS, FOR-FREIGHT, FLEXI-CROSS, EV-BAT, UPSIM, VITAL-5G, etc.): [email protected] / www.beia.eu
07/04/2023	MINDS & SPARKS GMBH	Austria	Expertise Request	Global call according to SRIA 2023 (RIA) (HORIZON-KDT-JU-2023-2-RIA-TOPIC-1)	F&T portal
M&S is an experienced project partner with a skilled team of researchers, engineers, developers and creatives offering APPLIED RESEARCH: Stakeholder Analysis, User Surveys, Requirements Engineering. DEVELOPMENT: Conception, Web Applications, Interface Design, Data Visualization, Piloting, Validation. DISSEMINATION & EXPLOITATION: Websites, Communication, Innovation and Technology Marketing, Solution Assessments, Market Analysis, Exploitation Planning. OUR PROFILE: http://bit.ly/mindsandsparks
07/04/2023	MINDS & SPARKS GMBH	Austria	Expertise Request	Pan-European network for Advanced Packaging made in Europe (CSA) (HORIZON-KDT-JU-2023-3-CSA-TOPIC-2)	F&T portal
M&S is an experienced project partner with a skilled team of researchers, engineers, developers and creatives offering APPLIED RESEARCH: Stakeholder Analysis, User Surveys, Requirements Engineering. DEVELOPMENT: Conception, Web Applications, Interface Design, Data Visualization, Piloting, Validation. DISSEMINATION & EXPLOITATION: Websites, Communication, Innovation and Technology Marketing, Solution Assessments, Market Analysis, Exploitation Planning. OUR PROFILE: http://bit.ly/mindsandsparks
06/04/2023	MINDS & SPARKS GMBH	Austria	Expertise Request	Focus Topic on Hardware abstraction layer for a European Vehicle Operating System (RIA) (HORIZON-KDT-JU-2023-2-RIA-FOCUS-TOPIC-2)	F&T portal
M&S is an experienced project partner with a skilled team of researchers, engineers, developers and creatives offering APPLIED RESEARCH: Stakeholder Analysis, User Surveys, Requirements Engineering. DEVELOPMENT: Conception, Web Applications, Interface Design, Data Visualization, Piloting, Validation. DISSEMINATION & EXPLOITATION: Websites, Communication, Innovation and Technology Marketing, Solution Assessments, Market Analysis, Exploitation Planning. OUR PROFILE: http://bit.ly/mindsandsparks
06/04/2023	Exeo Lab Srl	Italy	Expertise Request	Facilitate the engagement in global ICT standardisation development (CSA) (HORIZON-CL4-2024-HUMAN-01-61)	F&T portal
Exeo Lab is a partnership of policy specialists, with large experience in the areas of information technologies. We also provide SMEs and start-ups with advanced support in the field of digital and industrial technologies. We are interested in collaborating in the proposal writing and make available our national and EU network of partners and stakeholders. Please, contact us at [email protected]
06/04/2023	MINDS & SPARKS GMBH	Austria	Expertise Request	Improving the global demand supply forecast of the semiconductor supply chain (IA) (HORIZON-KDT-JU-2023-3-IA-TOPIC-1)	F&T portal
M&S is an experienced project partner with a skilled team of researchers, engineers, developers and creatives offering APPLIED RESEARCH: Stakeholder Analysis, User Surveys, Requirements Engineering. DEVELOPMENT: Conception, Web Applications, Interface Design, Data Visualization, Piloting, Validation. DISSEMINATION & EXPLOITATION: Websites, Communication, Innovation and Technology Marketing, Solution Assessments, Market Analysis, Exploitation Planning. OUR PROFILE: http://bit.ly/mindsandsparks
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Ayuntamiento de Benetússer	Spain	Expertise Request	SNS Societal Challenges (HORIZON-JU-SNS-2023-STREAM-CSA-01)	F&T portal
Benetússer Town Council, which belongs to the metropolitan area of Valencia, has its own department of European projects. We work transversally with the different areas in the Town Council, such as equality, youth, participation, education, environment, urbanism, employment and development, among others, as well as with the civic organizations of the metropolitan area. We can add value and help increase the quality of European projects. If you are interested, contact [email protected]
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	NUROMEDIA GMBH	Germany	Expertise Request	Improving the global demand supply forecast of the semiconductor supply chain (IA) (HORIZON-KDT-JU-2023-3-IA-TOPIC-1)	F&T portal
Nuromedia GmbH is a German software engineering & multimedia company with more than 15 years of experience in national and EU funded projects. Our team offers competences like software engineering, gamification, 2D/3D animation, UI/UX design, AR, MR & VR development, smart city, 5G, IoT, big data,digital twin and machine learning/AI. Our industry focus is Health, Energy, Telecommunication, E-learning, Education, Industry 4.0, Agriculture, Automotive. Contact info: [email protected]
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.
05/04/2023	Sima Sinaei	Vatican City	Expertise Request	Piloting emerging Smart IoT Platforms and decentralized intelligence (IA) (HORIZON-CL4-2024-DATA-01-03)	F&T portal
Distributed Artificial Intelligence Systems - Federated learning: Federated Learning (FL) is a distributed machine learning approach that enables devices in the computing continuum to collaboratively learn a shared model while keeping data locally. FL can be used to optimise the performance of AI models by leveraging data from across the continuum, while still ensuring data privacy by not sharing raw data. Techniques that shall be explored include stochastic gradient descent.