Study-unit Code
In all curricula
Valentina Franzoni
  • Valentina Franzoni
  • 42 ore - Valentina Franzoni
Course Regulation
Coorte 2023
Learning activities
Attività formative affini o integrative
Academic discipline
Type of study-unit
Opzionale (Optional)
Type of learning activities
Attività formativa monodisciplinare
Language of instruction
This course introduces students to the growing intersection of Artificial Intelligence, Neuroscience and Affective Psychology, known as Affective Computing. Students will gain interdisciplinary theoretical and practical knowledge on the detection and analysis of human emotions through Artificial Intelligence techniques, as well as the application of Affective Computing in different contexts, including robotics, health, education and entertainment. The ethical and social implications of Affective Computing and how these can be managed through the ethical responsibility of researchers and developers will also be explored. The course will involve the design and development of a research project in the field of Affective Computing to provide students with practical experience and application of the topics covered.
Reference texts
Study materials provided by the professor.
Book: Gender in AI and Robotics
The Gender Challenges from an Interdisciplinary Perspective.
Publisher:Springer Cham
Hardcover ISBN
Published: 02 March 2023
Softcover ISBN
Due: 16 March 2024
eBook ISBN
Published: 01 March 2023
Educational objectives
Understand the role of emotions in human communication and in relation to technologies
Acquire theoretical and practical knowledge about Affective Computing, understood as an interdisciplinary research field that combines Artificial Intelligence with Psychology and Neuroscience
Examine the applications of Affective Computing in different contexts, such as robotics, health, virtual and augmented reality, education and entertainment
Exploring the ethical and social implications of Affective Computing
Designing, and developing a research project in the field of Affective Computing
Useful but not indispensable to have taken and passed examinations in artificial intelligence and machine learning
Teaching methods
The course will be delivered face-to-face (and online where necessary and permitted), with theoretical lectures and practical exercises. Seminars and meetings with experts in the field will also be organised in order to deepen the course topics and discuss new research trends.
Other information
The lecturer is available for lectures, tutorials and examinations in English or Italian.
Learning verification modality
Assessment will be based on
- Active participation in lectures and practical exercises
- Development of an individual or group research project
- Oral presentation of the project at the end of the course
Extended program
Introduction to Affective Computing
- Definition and research areas of Affective Computing
- History and development of the field
- Role of emotions in human communication
Theoretical foundations of Affective Computing
- Theory of emotions and cognitive affective states
- Affective neuroscience
- Cognitive and emotional psychology
- Artificial intelligence and machine learning

Emotion detection and analysis
Methods of emotion detection, including:
- Human physiology detection (e.g., EEG, GSR, EMG)
- Recognition of facial expressions
- Voice and tone detection
- Detection of text semantics
Analysis of collected data and interpretation of information
Applications of Affective Computing
- Affective Robotics
- Mental health and well-being
- Education and customised learning
- Virtual and augmented reality and entertainment
- Marketing and advertising
- Other application fields of Affective Computing
Ethical and social implications of Affective Computing
- Privacy and data security
- Social impact of affective technologies
- Limits and risks of Affective Computing
- Ethical responsibility of researchers and developers
Obiettivi Agenda 2030 per lo sviluppo sostenibile
The course responds to the objectives of the Agenda 20230 for Sustainable Development, in particular the following goals
No. 3 Health and well-being
no. 4 Quality education
no. 5 Gender equality
no. 9 Industry, innovation and infrastructure
no. 10 Reducing inequalities
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