Research Seminar on Intelligent Systems and Human-Centric Computing

Recommended Prerequisites

Research Methods I (1st semester, 6 ECTS, mandatory).

Teaching Methods

Three complementary activities will be carried out:

1 - Lectures (9h): to introduce to current topics in the scientific area.

2 - Seminars (24h): presentation and discussion of scientific papers by students.

3 – Peer-reviewing, presentation and discussion in a workshop.

Evaluation:

- Active participation in the seminars: 20%

- Quality of the reviews: 30%

- Written exam with questions on the papers discussed in the course: 50%

Attendance to 75% of the total classes is mandatory.

Learning Outcomes

• To obtain an overview of the state of the art and main research challenges of the scientific area of the course.
• To obtain knowledge and understanding about research projects and topics of the scientific area of the course under different perspectives, including scientific, methodological, management and communication.
• To improve competences of critical analysis of scientific works, synthesis, scientific writing, verbal and writen communication, critical reasoning, autonomous learning, research and group integration.

Work Placement(s)

No

Syllabus

Advanced topics selected from the vast area that may include the following:

• Machine learning
• Data pre-processing
• Feature engineering
• Pattern recognition and data stratification
• Classification and prediction models
• Model evaluation
• Evolutionary computation
• Optimization
• Complex systems
• Computational design
• Computational creativity
• Digital media and education

Other topics may be analysed and discussed, within the vast area of Intelligent Systems and Human-Centric Computing.

Head Lecturer(s)

Luís Filipe dos Santos Coelho Paquete

Assessment Methods

Assessment
Active participation in the seminars: 20.0%
Quality of the reviews: 30.0%
Written exam with questions on the papers discussed in the course: 50.0%

Bibliography

Para cada tópico abordado na disciplina será fornecida aos alunos uma lista de artigos de investigação.

For each topic to be addressed in the course, a list of research papers will be provided to the students.