Structure /


The main objectives of the Center of Intelligent Systems focus on research & development activities in four complementary activities:
  1. Fundamental research,
  2. Systems development and applications,
  3. Transfer of technology to industry, and
  4. Post-graduate education (supervision of PhD and MSc students).
Headed by Prof. João M. Costa Sousa, the research activity of the Center of Intelligent Systems aims the multidisciplinary interplay of systems and control theory, and engineering applications in the areas of:
Intelligent Data Modelling and Optimization
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The research activities in INTELLIGENT DATA MODELLING AND OPTIMIZATION are coordinated by João M. Costa Sousa. This research area addresses the development of models and decision support systems based on intelligent methodologies. As data gets big and complex, there is a need for multidisciplinary approaches to transform data into knowledge. This transformation allows analysis, learning, knowledge extraction and modeling in very different domains, including engineering, biomedicine or environment. This research area involves the design of intelligent models and algorithms and the development of decision making models to form classifiers personalized diagnosis, patient treatment systems, and process modeling systems.
Mechatronic Systems
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The research activities in MECHATRONIC SYSTEMS are coordinated by Paulo Oliveira. This research area focuses on a new design paradigm that intertwines the mechanical, electronic and computer engineering domains, under a common systemic framework, resulting in synergistic solutions to tackle complex challenges of societal relevance. Development of fleets of robotic vehicles, in ground, aerial, and marine scenarios, cooperative and hybrid human/robotic manipulation systems, medical and service robots and artificial muscle technology for biomedical applications are examples of developments pursued. This research targets the advancement of robotics technology in three focal areas: development of targeted interventional procedures, which require the merging of medical imaging algorithms with high precision robotic devices; development of assistive technical aids for aged persons or for the impaired; and development of guidance, positioning and navigation systems using new platforms and challenging scenarios. These challenges are addressed using new sensors, actuators, embedded systems, and adaptive materials, leading to revolutionary mechatronic solutions.

Networked Distributed Systems
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The research activities in NETWORKED DISTRIBUTED SYSTEMS are coordinated by Miguel Ayala Botto. This research area addresses the concept of networked systems applicable to engineering systems in order to enhance its performance and security. Many infrastructures and service systems of the present day society can naturally be described as networks of a huge number of simple interacting units. The availability of reliable and fast communication solutions motivated the decentralized management of spatially distributed systems. This research area focuses its expertise in the research in: smart energy management, including renewables, power systems, urban transport, buildings and energy storage; distributed optimization of supply chains and supply networks using advanced bio-inspired algorithms; fault tolerant control in networked control systems based on multi-agents systems; control of multi-robot networks; distributed control applied to agriculture and industry; distributed estimation for sensor networks; network systems in biology.
Systems Engineering in Life Sciences
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The research activities in SYSTEMS ENGINEERING IN LIFE SCIENCES are coordinated by Susana Vinga. This research area focuses on the identification of bio-systems, systems biology, systems medicine and translational medicine. The rise of genomics and accumulation of heterogeneous amounts of biological and biomedical data is driving the emergence of a new systems based approach to life sciences. The foremost question in Systems Biology and Medicine is how to explain the complexity of living organisms by integrating multiscale data from physiological experiments. Systems engineering is playing a central role in unraveling this structure and understanding the behavior of complex organisms, with direct applications to interpreting physiological systems through a mathematical and computational perspective. For more information please visit