General Information

Welcome to (PPGI) at Ufes

  • From a technical point of view, an information system can be defined as a set of interrelated components that collect, process, store and distribute information. From an organizational point of view, an information system is a solution based on information technology aimed at supporting organizations both in their daily activities and in their decision-making.

    The development of information systems involves several aspects ranging from the understanding of the domain to be considered by the system until its use by the organizations. In this sense, the line of research Information Systems includes the investigation of topics related to the development of various types of information systems, taking into account the particularities of the different types of organizations to which the systems are intended.

    To this end, research is developed within the following sub-areas:

    Software Engineering: addresses topics related to technologies, methodologies and tools for the development and maintenance of software. It includes research that mainly addresses: software processes, software quality, software measurement, statistical process control, knowledge management, project management and software development environments.

    Conceptual Modeling and Ontologies: Investigates the development and application of domain ontologies, foundational ontologies and ontology-based techniques in various contexts of conceptual modeling, such as: information modeling, organizational modeling, corporate architectures, semantic interoperability, agent-based systems and the Semantic Web.

    Databases: includes the investigation of techniques, methods and tools for data storage, information retrieval, data mining, data integration, knowledge discovery and recommendation systems.

    Computer Science in Education: approaches the development and application of tools, techniques and methodologies for teaching-learning. It includes works related to virtual learning environments, distance education, intelligent tutor systems and languages for knowledge representation.

  • The line of research in optimization brings together researchers, teachers and students involved in research projects in the optimization area. In this line, combinatorial optimization research is carried out, such as the development of logistic models and optimization for the productive sector, the implementation and adaptation of heuristics and metaheuristics for problems modeled in graphs and the development of applications modeled by Networks Flows, among others.

    Research is developed within the following sub-areas:
    - Heuristics and meta-heuristics;
    - Graph-based Algorithms;
    - Evolutionary Computing;
    - Combinatorial Scientific Computing;
    - Transportation Networks;
    - Location Search;
    - Numeric Analysis.

  • In this line of research we are interested in investigating the theoretical basis, methodologies, languages and tools for solving complex problems, such as the problems known as algorithmically intractable (NP-complete or worse) and ill-defined (non-arithmetical) problems.

    The resolution of these problems can be studied from three main axes: (a) methods of reasoning (search methods); (b) representation of knowledge; (c) learning mechanisms.

    Among the main theoretical approaches considered in our research, we highlight: (a) logical systems (classical logic, temporal logic, fuzzy logic, etc.); (b) neural networks; (c) evolutionary computation; (d) ontologies.

    On the other hand, some application classes have specific characteristics due to the importance of these problems in relevant situations in real life as well as the demand for specific methods.

    The faculty has developed projects in the following application areas: (a) computer vision; (b) natural language processing; (c) image processing; (d) knowledge-based systems; (e) intelligent design; (f) intelligent environments to support education; (g) automatic proof of theorems; (h) pattern recognition; (i) intelligent retrieval of information.

  • The term High Performance Computing has been widely used to characterize the use of computing resources that are approximately an order of magnitude higher than commonly available features such as desktops or workstations.

    This definition encompasses not only computers, but also the network technology, algorithms, and environments required to enable the use of these systems, which can range from clusters of PCs to large vector supercomputers.

    Currently, the term supercomputer has been gradually replaced by the High-Performance Computing platform. Nowadays, these systems already surpass the Teraflops barrier, and the latest forecasts indicate that before the end of this decade there will be systems with processing capacity superior to the Petaflops barrier.

    Thus, scientists have experienced a large increase in processing capacity in recent decades, allowing the solution of problems that were once considered intangible.

    However, problems such as global climate prediction, sequencing of the human genome and simulation of flow in real-scale oil reservoirs are examples of applications that still pose a major challenge to the scientific community. Therefore, a lot of research work has been carried out in this line of research in order not only to improve the architecture and performance of the systems, but also to allow more efficient use of the available computational resources.

    Research is developed within the following sub-areas: Scientific Computing, Computer Architecture and Parallel Algorithms.

  • In this line of research we are interested in investigating concepts, methodologies and techniques in distributed systems and applications, wired or wireless computer networks, multimedia and Web-based Systems, Collaborative Systems, Ubiquitous and Pervasive Computing. Research is developed within the following sub-areas:

    Distributed Systems and Applications: (1) infrastructure, services, applications and performance evaluation, grid computing, clusters and cloud computing; (2) Specification, Verification, Implementation and Tests for Distributed Systems and Communication Protocols; (3) Modeling and performance evaluation of distributed systems (4) Synchronization.

    Computer Networks: (1) infrastructure, wireless networks and mobility, sensor networks, performance analysis, network applications; (2) Methodologies and Conception Techniques, Analysis and Design of Computer Networks (3) Content Defined Networks (CDN), Software Defined Network (SDN), Data Center Network, Home Networking (4) Virtualization.

    Multimedia and Web-based Systems: (1) Content Recovery, Information Visualization, Personalization, Accessibility; (2) Models and Tools for Distributed Multimedia Systems and Applications, Interactive Digital TV Applications, Synchronization; (3) Collaborative Systems, Crowdsourcing, Social Web; (4) Ubiquitous and Pervasive Computing, Multimodality, Performance Evaluation and usability.

    The faculty has developed projects on the following topics:
    (a) Digital Cities; (b) Intelligent Cities; (c) Digital Video; (d) Digital TV; (e) Data Center Networks; (f) Multimedia synchronization; (g) Collaborative Systems; (h) information retrieval and visualization.

Welcome to the UFES Postgraduate Program in Computer Science!

The Postgraduate Program in Computer Science fosters the scientific development of researchers and higher education professors. With a long history of excellence in postgraduate education, the program brings together scholars from diverse fields within computer science performing cutting edge research, thus contributing to professional enhancement in public and private organizations.

Based at the Technology Faculty of the Federal University of Espírito Santo, the Postgraduate Program in Computer Science was established in 1994, with the creation of the master's degree. Through the rise in scientific output, the doctoral degree was accredited in 2010. Since its accreditation, the program has awarded 325 masters, five doctoral degrees and has 85 master’s and 37 doctoral students currently enrolled.

The program is based in Vitória-ES, offering the course of **MSc in Computer Science** since 1994 e the course of **Doctoral Degree in Computer Science** since 2010 and has an academic qualification profile certified by CAPES, receiving 4 on its last evaluation.

The program already has 337 masters and 9 doctors and counts with 109 students regularly enrolled, being 69 in the masters and 40 in the doctorate.

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