Business partners

C3DNA Inc

Periodo: 2013-2018

Activities:

  • Project management;
    Progettazione e sviluppo software (Middleware per la gestione di applicazioni distribuite in ambiente Multi Cloud) ;
  • Progettazione ed implementazioni di Data Pipeline ETL/ELT;
  • Progettazione ed implementazioni di un Decision Support System AI-based (ML/DL) a supporto delle attività di controllo della QoS dell’appplicazione sviluppata.
  • Monitoraggio e controllo della QoS del software sviluppato;
  • Training e supporto.

Agile Srl

Periodo: dal 2014

Activities: 

  • Progettazione e sviluppo software (Dashboard AI-based per il supporto alle decisioni in ambito amministrativo ospedaliero e per la data exploration -tramite smart dashboard - in ambito sanitario);
  • Progettazione e implementazione di Datalake Sanitari;
  • Progettazione ed implementazioni di Data Pipeline ETL/ELT;
  • Progettazione ed implementazioni di un Decision Support System AI-based (ML/DL) per l’estrazione di informazioni relative alla “gestione della qualità dei processi” dai diversi database e dalla cartella clinica.

Verge Technologies Inc

Periodo: 2016 onwards

Activities: 

  • Project management;
    Progettazione e sviluppo software (Middleware per la gestione la gestione consistente e scalabile di repliche di diversi database SQL, NoSql e Object Storage);
  • Progettazione ed implementazioni di un Decision Support System AI-based (ML/DL) a supporto delle attività di “performace and cost management” dei database gestiti;
  • Implementazione di politiche di  High Availability and Disaster Recovey;
  • Monitoraggio e controllo AI-based della QoS del software sviluppato;
  • Training e supporto.

Platina Systems Inc

Periodo: 2018 onwards

Activities: 

  • Project management;
    Progettazione e sviluppo software(Middleware per la estione di risorse computazionali, di storage e di rete);
  • Gestione di un cluster Ceph di oltre 35 Petabyte e 2500 dischi;
  • Realizzazione di una soluzione Metal-as-a-Service;
  • Progettazione ed implementazioni di un Decision Support System AI-based (ML/DL) per migliorare le performance e la robustezza del software open-source Ceph;
  • Monitoraggio e controllo della QoS del software sviluppato;
  • Training e supporto.

Legalock Srl

Periodo: 2016-2018

Activities: 

  • Project management;
    Progettazione e sviluppo software (Applicazione software per la gestione e la verifica dell’identità/KYC basata du tecnologie biometriche);
  • Progettazione di un sistema di riconoscimento facciale multi-frame  basato su AI;
  • Monitoraggio e controllo della QoS del software sviluppato;
  • Training e supporto.

Sendata LLC

Periodo: 2020 onwards

Activities: 

  • Project management;
    Progettazione e sviluppo software (Sviluppo di un Object Storage S3-compatible su tecnologie blockchain/web 3.0 - Sviluppo di un data catalog per datalake in ambito blockchain/web 3.0);
  • Progettazione ed implementazioni di Data Pipeline ETL/ELT  su tecnologie web 3.0; 
  • Training e supporto.

Research Projects 

ADAI

NextGeneration EU  

https://next-generation-eu.europa.eu/

Project Time Window: In progress

Role: Consultant

Focus on: RAG, LLM, DTx, Datalake, Data Pipeline engineering

Summary

ADAI (Assistenza Domiciliare in Ambienti Intelligenti - Home Care in Smart Environments) is a project connected to the main initiative, RAISE (Robotics & AI for Socio-economic Empowerment). ADAI focuses on developing a Clinical Assistance Ecosystem for managing home-based digital therapies using Assistive Robots and Clinical Predictive Systems powered by Artificial Intelligence

SENDATA (?) - 2020

PLATINA SYSTEMS INC

VERGE TECHNOLOGIES INC

AGILE SRL

VESPA 2.0

PO FESR Sicilia 2014-2020 

http://www.euroinfosicilia.it/

Project Time Window: 2019-2023

Role: Partner

Focus on: Big Data Management, Data Analysis, Data Pipeline engineering

Summary

The project “Virtual Environment for a Superior neuro-Psychiatry” Second Generation (VESPA 2.0) continues the previous efforts to promote health and use innovative solutions for the psycho-physical well-being of individuals with greater vulnerability and neuro-fragility. The primary research areas focus on the analysis, revision, and adoption of: technologies and models for cognitive stimulation and learning; user-centered technologies and application models aimed at improving the quality of life (health, safety, mobility, social inclusion) of identified end-users; innovative technologies, products, and service models to promote healthy lifestyles. The VESPA project has developed and validated in the laboratory a high-immersion 3D Virtual Reality (VR) system, remotely supervised by healthcare personnel located in remote facilities, for the quantitative evaluation and rehabilitation of cognitive-motor functions in patients with Intellectual Disabilities (ID), Communication Disorders (CD), or Alzheimer’s Disease (AD).

VESPA 2.0 aligns with broader strategies by introducing new products, fostering innovation, and exploring international markets. The integration of intensive computing, Big Data, and advanced VR technologies strengthens its impact and supports its evolution towards comprehensive, user-centered healthcare solutions, including home use.

Deep Learning for Health

PO FESR Sicilia 2014-2020 

http://www.euroinfosicilia.it/

Project Time Window: 2019-2022

Role: Partner

Focus on: IA-based solution for Health-related data, Patient treatment, Graph-based knowledge management, Big Data Management, Data Pipeline engineering

Summary

The project, funded by the European Union throught the European Regional Development Fund (FERS - Fondo Europeo per lo Sviluppo Regionale), focuses on research and development to create an advanced prototype designed to support healthcare professionals in identifying key variables that influence the clinical behavior of patients in high-complexity care settings. This innovative approach leverages cutting-edge technologies in Deep Learning, Big Data, and computational processing to deliver actionable insights in real-time.

Data for the project were sourced from selected hospital departments, which played a crucial role in the experimental phase. These data were meticulously collected, pre-processed, homogenized, and organized into a graph-based database to ensure consistency and relevance. This structured repository facilitates comprehensive analysis, enabling deep learning algorithms to extract meaningful patterns, correlations, and insights.

The graph-based database enhances the ability to represent complex relationships among variables, offering a more nuanced understanding of clinical dynamics. The prototype aims to improve decision-making processes, enhance patient care, and optimize resource utilization in complex healthcare environments by adopting this data-driven approach.

 

 

WIKI Roads Map

National R&D Project 2014-2016

Role: Consultant

Focus on: IA-based solution for traffic management, collision avoidance and  

Summary
WikiRoads Map is a Research and Development project funded by the PAC funds of MIUR – the Italian Ministry of Education, University and Research. The project aims to create a collaborative system that leverages, in an innovative and integrated manner, the data flow generated by road infrastructures and the surrounding territory. It applies semantic analysis technologies for the extraction, collection, integration, and publication of data.