Programme StructureThis PhD Programme is organised in three phases: Preparation, Research, and Writing Up. The programme has typically a total duration of four years, but the duration of the research and dissertation writing phases may vary, but a student will not be allowed to enrol in the programme for more than 6 years. PreparationIn the preparation phase, expected to span from 12 to 18 months, the students should
Upon enrolment, all students are assigned individual tutors by the PhD Programme Committee (among the lecturers of the programme) that will support them, in particular in the selection of units of the PhD course. Tutors are eventually replaced by PhD supervisors, chosen by mutual consent, that will support the preparation of the Thesis Plan, and subsequently supervise their research work. The candidates must present their Thesis Plan publicly before an Advisory Committee, composed by their supervisor(s) and two other specialists in the specific area of research. Upon completion of the PhD Course, students are entitled to receive a “Diploma de Estudos Avançados”. ResearchUpon approval of their Thesis Plan, students should carry on with their supervised research work. After the first year, the student must present a progress report to the Advisory Committee. After two years, the student must prepare and submit a Thesis Proposal. The purpose of this document, that will be orally presented and formally reviewed and evaluated by the Advisory Committee, is to assess the maturity and results of the work already produced, and to determine whether the student will be able to produce the final written dissertation after another year of full-time work. Writting UpAfter the “Thesis Proposal” is approved the student may enter the final phase of the PhD Programme, the dissertation writing up phase. This final phase is not supposed to be exclusively dedicated to dissertation writing, so that the student is expected to extend or review results already produced as a result of the “Thesis Proposal” evaluation. PhD CoursesThe PhD Course structure is presented in the table below. Two units are mandatory: Research Seminars and Technical and Scientific Communication. Students must obtain, at least, 12 credit points in advanced units. For each area, several units will open each year: the list of units proposed for 2008/09 is presented in the table. Students wishing to obtain the 12 credit points in the same area should take the Advanced Studies unit, which can be instantiated with any other unit. Students must additionally obtain, at most, 12 credit points in complementary units. The “Complementary Studies” and the “Free Studies” units can be instantiated with units from other graduate programmes in the University or units of affiliated or joint graduate programmes. The “Free Studies” units can additionally be instantiated with other activities relevant to the student work, such as participation in Summer/Winter Schools.
PhD Courses descriptionArtificial IntelligenceKRRA - Knowledge Representation, Reasoning and AgentsLecturers: José Júlio Alferes, Carlos Damásio, João Leite Description: The
course provides the fundamental basis for advanced study of
state-of-the-art knowledge representation and reasoning formalisms, and
surveys state-of-the-art work in this area, exploring applications to
the Semantic Web and to Multi-Agent Systems. CP – Constraint ProgrammingLecturers: Pedro Barahona, Francisco Azevedo, Jorge Cruz, Ludwig Krippahl Description: The
course addresses state of the art constraint programming technology
that has recently made it possible to solve efficiently combinatorial
problems of non trivial complexity, in several domains such as finite
domains, sets, graphs and continuous domains, as well as specific
domains (e.g. in bioinformatics). MLKE - Machine Learning and Knowledge ExtractionLecturers: Nuno Marques, Susana Nascimento, Joaquim Ferreira da Silva, Gabriel Pereira Lopes Description: This
course addresses several machine learning and data mining methods,
surveying both theoretical and practical aspects of these methods, and
discussing open research directions in this area. This should allow
students to develop new algorithms or adapting those studied, to
understand and change learned models for specific problems and apply
the methods to new problems assess the results obtained. Computer Graphics and MultimediaCGM - Computer Graphics Modelling Lecturers: Próspero dos Santos, Fernando Birra Description: The
main focus of this course will be the domain of modelling suitable
to the generation of synthetic images, either static or dynamic (i.e.,
for computer animation) and at several levels of interaction. IVME - Interaction and Visualization in Multimedia Environments Lecturers: Nuno Correia, Adriano Lopes, Teresa Romão, Armanda Rodrigues, Sofia Cavaco Description: Digital
media consumption and production is an important part of many
professional and personal activities. The course addresses the areas of
media processing, visualization and interaction, and provides an
overview of the main topics of media representation and how it is used
in different computational and programming frameworks. It also
discusses how to combine heterogeneous media in hypermedia structures
and its extensions to narrative models and repurposing tools. Computer Systems and NetworksCSCS - Computer Systems and Communications Security Lecturers: Henrique João, Sérgio Duarte Description: The
course provides a research-oriented broad and deep knowledge about
new security problems, new adversarial models and new trustworthy
conditions related to malicious and selfish distributed computing
environments. These environments include new and emergent network
technology and new experimental large scale distributed settings, such
as, MANETs (mobile and ad-hoc networks), WSN (wireless sensor networks)
and mesh-based or p2p internetworking technology. PGAC - Parallel, Grid and Autonomic Computing Lecturers: José Cardoso e Cunha, Pedro Medeiros, Vitor Duarte, Cecília Gomes Description:
Large-scale applications including e-Science Grand Challenges
increasingly require forms of parallelism and distribution with large
volumes of data. These applications execute in the presence of
uncertainty, partial knowledge, unpredictability, adversity, and
dynamic change (a consequence of the diversity of current cluster and
network / grid computing platforms). Lecturers: Nuno Preguiça, João Lourenço Description:
Transactional processing mechanisms have been used for many years in a
large number of systems, notably in database management systems and
more recently as a concurrency control mechanism for multicore
computers. Information Systems TechnologyIST - Information Systems TechnologyLecturers: António Porto, Carlos Damásio, João Moura Pires Description: The
dawn of the Web originated new opportunities, applications and
challenges for information systems. The increasing complexity demands
new formalisms, techniques and methodologies, as is the case of the
integration of services at the global scale over the Semantic Web,
requiring a new Services Sciences, Management and Engineering (SSME). Programming Languages and ModelsADSIR - Algorithms and Data Structures for Information Retrieval (PLM) Lecturers: Margarida Mamede, Luís Russo, Fernanda Barbosa Description:The
course addresses algorithms and data structures for
performing
information retrieval. The search can be either to match corresponding
objects or to find similar objects from a larger set.
The exact matching problem is important for a wide range of applications (e.g. word processors). However the established solutions for small applications do not scale up to process the massive amounts of text appearing in Information Retrieval systems, web search engines, or molecular sequence databases. The course addresses this problem, both on-line and with indexing data structures (a very active area of research), focussing on the impact of succinct and compressed data structures in the performance of these indexes. The course also studies several data structures for coping with the problem of matching similar objects in high-dimensional domains, relevant to many applications, such as natural language dictionaries, databases of DNA or protein sequences, databases of images, multimedia databases, and geographic information systems. CCPL - Communication and Concurrency-Centric Programming Languages Lecturers: Luís Caires, Carla Ferreira, João Seco Description: With
the advent of pervasive concurrency and communication centric
software, both at the small scale (multicore processors), and at the
large scale (distributed web services), new programming language
abstractions are being proposed, together with related static analysis
techniques based in type systems, logics, or finite-state model
checking, able to certify key properties of software without actually
running the programs, so that defects may be caught as early as
possible. Software EngineeringASD - Advanced Software Development Lecturers: Ana Moreira, João Araújo, Vasco Amaral Description: A
primary challenge of Software Engineering is the taming of
ever-increasing complexity in software systems. Advanced Software
Development (ASD) focuses on this challenge, by covering
Aspect-Oriented Software Development (AOSD), Model-Driven Development
(MDD) and Software Product Lines (SPL). ESE - Experimental Software Evaluation Lecturers: Fernando Brito e Abreu, Miguel Monteiro, Vasco Amaral Description: This
course will help candidates in setting up experiments to raise
statistical evidence on the validity of their proposals (e.g. methods,
techniques and/or tools) by applying the scientific method. The course
is outlined as follows. First we will review some techniques for
supporting domain knowledge formalization. Then, students will learn
how to perform hypothesis elicitation in the context of Software
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