Programa de Pós-Graduação em Computação

Bioinformatics

The main goal of the research line is to develop and apply bioinformatics algorithms and tools. The union between computing and biology enables a paradigm shift in the study of biological systems. Computation allows the large amount of data obtained from biological systems to be processed in a reasonable time enabling quick answers to questions that would take months to be answered in in vitro experiments.

 The use of mathematical and computational methods is becoming an integral part of biological research. Although in recent times great advances have been made in this area, there are still several questions to be answered or refined. One of the great challenges lies precisely in the analysis of huge amounts of complex data from which useful and reliable models of biological processes can be generated.

 This research area has a strong interaction with other areas of the program, more specifically with Soft Computing and Multi-agent Systems. In addition, there is also collaboration with the Graduate Program in Health Sciences, Mycobacteria Laboratory.

 The possible applications of Bioinformatics are numerous and important. In this area of research it is intended to specifically research theories, models, methods and techniques in:

• Molecular dynamics
• Molecular docking and virtual screening
• Protein Folding
• Genetic regulatory networks
• Biological data mining
• Simulation of biological systems

Graduates of Bioinformatics research area will have a solid background in computational and statistical methods applied to biological field and will be able to contribute to the advancement of science in this area. In addition, the contributions obtained may be applied to other areas of science.

Digital and Embedded Systems

 This are addresses topics of Computing Systems, with the main focus on Digital Systems, Distributed Systems and Embedded Systems. These systems can be considered strategic within the exact sciences and engineering. Such systems are present in almost all of the currently industrialized products, representing an important added value in the national and world economic scenario. The mastery of device design and manufacturing technologies and the implementation of systems are key elements for the development of industry and research, in all areas of knowledge.

Research and development are carried out on the following topics:

• Design of micro and nano systems;
• Development of integrated circuit design assistance tools;
• Digital Systems Design Project;
• High energy efficiency systems design project;
• Fault-tolerant system design project;
• Assessment of the reliability of nanotechnologies;
• Parallel and distributed programming;
• Distributed systems;
• Replication and fault tolerance on distributed systems;
• Development and verification of competing systems.

Intelligent Robotics and Automation

 The objective of this research area is the development of new computational techniques and algorithms for analysis, modeling and control of sensor networks and actuators, whether these constituents of automation are systems or grouped in Robotic Systems.

More precisely, it seeks to study the computing involved in engineering projects capable of allowing the construction of artifacts with distributed and autonomous perception, decision-making and action capacity, in real, virtual and /or mixed environments.

To this end, the areas of the Soft Computing and Digital Systems and Embedded Computing, will provide theoretical subsidy  for the treatment of the various aspects of Computer Engineering that are associated with the construction of Automation and Robotics Systems, intelligent and present in Real-world and/or Virtual Environments such as the treatment of uncertainty, learning, dissemination, control, communication protocols, planning and scheduling, mapping and localization, mixed reality, real time systems, embedded computing - and its efficient solution - will be discussed in this research area.

In the research area of Automation and Intelligent Robotics, it is intended to research theories, models, methods and techniques in:

• Computational Systems and Technologies for Environmental Perception:
  • Acquisition and Sensory Information Treatment, Models for representation and description of environment, Recognition and Interpretation of Sensory Information (mapping, location, tracking);
• Computational Systems and Technologies for Control and Performance in Environments:
  • Control, Navigation, Planning and Staggering Systems
• Architectures for Sensor Networks and Actuators:
  • Architectures for (multi) Robots, Automation Systems (buses, rfids, scadas). Manufacturing Systems. Ubiquitous Systems.
• Mixed Environments:
  • Virtual and Mixed Reality, Teleoperation, Simulation and Synthesis of Environments, Dual Worlds (telepresence and teleoperation), Internet of Things. Reconstruction.

Educational Technologies

The advent of interaction and communication technologies stimulates education in order to diversify the forms of teaching-learning and the bi-directionality of knowledge, gathering a number of resources to support communication, interaction and cooperation in the educational context.

This area of research has a multi and interdisciplinary approach with the main objective of applying technologies of interaction and communication in education, empowering the student to learn aspects which are inherent to the theoretical-practical content, with the themes proposed from these experiences, mediated by face-to-face and online Educational Technologies. It interacts with other program areas, more specifically with the Information and Communication Technologies in Education Graduate Program (TICEDU) and the Health Sciences Graduate Program.  We intend to investigate the educational and assistive technologies, specifically the theories, models, methods and techniques of the following themes:

• Development of computer systems and resources;
• Education and Social Assistive Technologies in the context of digital inclusion;
• Software engineering in educational environments;
• Topics in learning objects;
• Usability and accessibility in educational software;
• Human-Computer Interface in educational environments;
• Virtual and Augmented Reality in education;
• Robotics in education;
• Simulators and educational games;
• Mobile Learning;
• Assistive Technologies applied to Special Education
• Dual environments in the Teaching-Learning process

Graduates of this research area make it possible to raise the conceptions of Educational and Assistive Technologies used as a complementary resource for the improvement of the educational process to pedagogical practice, aiming at the quality of Education.

Multi-agent Systems

 The area of Multi-agent Systems resulted from the incorporation of the concept of "autonomous agent" to distributed Artificial Intelligence systems. Multi-agent systems have become a viable alternative to modeling and implementing complex systems.

 Research in Multi-agent Systems involves the investigation of theories, models, techniques and implementation platforms of agents and multi-agent systems and their use in the resolution of complex applications, going through the methodological area of Agent-Oriented Software Engineering.

The Multi-agent Systems Research area aims to operate as a partner of all other research areas. In particular, it intends to contribute:

• for the automation and Intelligent Robotics area, through the application of the agent concept to design in distributed manufacturing environments (Automation) and to multiple robot systems (Intelligent Robotics);
• for the line of Embedded and Digital Systems, through the use of agent-oriented programming in the development of embedded software;
• for the Soft Computing area, both in the form of a case study area for modeling and analysis of complex systems, and in the form of an area of application of flexible theories and models to the construction of systems that operate with inaccurate information.

In the Multi-agent Systems research area it is intended to research:

• agent models: cognitive models, models based on decision theories, hybrid models
• models of organization of agent systems: organizations, institutions, agent societies
• models of coordination and regulation of interactions: exchange values, game theory and decision
• models of agent societies: social, cultural, economic, political aspects, etc.
• agent-based systems specification methodologies: formal specification of agent systems
• agent-oriented programming: multi-robot systems, distributed manufacturing systems
• agent-based simulation models and methodologies: for agent-based social simulation, for agent-based environmental simulation

• Soft Computing

   

  Soft Computing became particularly important since the early 90s, when there was a growing interest in modeling more complex systems, which began to emerge in areas such as biology, medicine, Humanities, Management Sciences, Social Sciences, Engineering, etc., which often present themselves intractable for mathematics and conventional models.

   

  Soft computing research involves the development of theories, models, techniques, methods and software that offer solutions tolerant to subjectivity, imprecision, uncertainty, incomplete, partial or conflicting information, partiality of truth and partiality of possibility, which appear in the modeling of complex systems and/or imperfect information, so common in the context of Engineering in general, in particular, Computer Engineering. The objective is to seek approximations or combinations of different theories, models, techniques and methods that are able to adequately reflect the imperfection, achieving treatability, robustness, reliability and reasonable cost solutions.

   

  In the XAI era (eXplainable Artificial Intelligence) - explanatory Artificial intelligence, considering that interdisciplinarity, the large volume of data, and the dynamics of diverse applications increasingly require that the method and results are explainable to all, soft computing, for its models based on linguistic variables (and not numerical), qualified by linguistic terms, is considered the area that has a fundamental role for the much desired explicability.

   

  This line of research is intended to serve as the basis for all other research areas. For example, it can support research into hybrid intelligent systems for robotics and automation (fuzzy neural networks, fuzzy perception in robots, interval methods for computer vision, etc.), as well as for research in multi-agent systems (hybrid agent models in general).

   

  In particular, soft computing becomes important for the development of complex system applications, as well as for experiment projects and reliability analysis, such as in the Simulation of Social and Environmental Systems, in Computational Biology, in Computing and Automation Technologies, among others.

   

  In the area of Soft Computing research, it is intended to research theories, models, methods and techniques in:

   

  • Fuzzy and interval computing: interval Mathematics, fuzzy sets and logic, fuzzy systems;
  • Bio-inspired computing: evolutionary systems, neural networks, machine learning;
  • Computing for data science: data mining, big data, deep learning, classification, decision making;
  • Applications in the most diverse areas.