About the Artificial Intelligence Doctoral Ecosystem

The Ingenium Doctoral Ecosystem in Artificial Intelligence connects leading universities to create a collaborative platform for advancing research in AI, machine learning, quantum computing, cybersecurity, and sustainable development.

By fostering interdisciplinary collaboration across diverse fields like robotics, human-centered AI, natural language processing, and cyber-physical systems, the ecosystem integrates expertise from areas such as economics, law, cognitive science, and engineering.

Supported by cutting-edge research infrastructure, specialized labs, and strong academic-industry partnerships, this ecosystem serves as a hub for groundbreaking innovations aimed at addressing global challenges.

The ecosystem’s dynamic environment drives research in high-impact areas such as healthcare, smart cities, Industry 4.0, and environmental sustainability

Disciplines Involved

  • Computer Science;
  • Engineering;
  • Mathematics and Statistics;
  • Cognitive Science and Psychology;
  • Ethics and Philosophy;
  • Data Science;
  • Biomedical Sciences.

Goals of the AI Doctoral Ecosystem

The goals of the Ingenium Doctoral Ecosystem are to foster interdisciplinary research in AI and related fields, promote scientific discovery, and drive technological advancements with real-world applications.

Core Research Areas

  • Artificial Intelligence (AI) and Machine Learning

    This area includes trustworthy and explainable AI, natural language processing (NLP), computer vision, neural networks, deep learning, GANs, and reinforcement learning, with applications spanning healthcare, social sciences, robotics, and economic modeling.

  • Quantum Computing and Cybersecurity

    Research in this domain covers quantum networks, quantum-cybersecurity, IoT security, and bioinformatics, with a strong emphasis on cyber-resilience, cybersecurity standards, and data protection.

  • Human-Centered AI and Human-Robot Interaction

    This area explores AI in human-robot interactions, social robotics, and autonomous systems, with a particular focus on user-centric designs for healthcare, education, and smart cities.

  • Digital Health and AI in Healthcare

    This research focuses on developing AI-driven healthcare technologies, leveraging data analytics for disease prediction, personalized treatment, and healthcare management, alongside the exploration of ethical frameworks in digital health.

  • Cyber-Physical Systems and Internet of Things (IoT)

    Research here investigates smart cities, Industry 4.0, and sustainable mechatronics, focusing on the integration of IoT and robotics for industrial and environmental applications.

  • Sustainable Development and Engineering

    This area focuses on integrating AI and digital transformation for sustainable systems, energy optimization, and industrial processes, aiming for innovative solutions to global sustainability challenges.

AI Doctoral Board

The AI Doctoral Ecosystem has a dedicated Doctoral Board, responsible for defining educational components, including seminars, methodological workshops, and theoretical training.