PhD in Computer Science

Intelligent User Interfaces

Intelligent User Interfaces

Academic year 2018/2019

Sommario del corso

• Course objectives
• Results of learning outcomes
• Course delivery
• Learning assessment methods
• Support activities
• Program
• Suggested textbooks and readings
• Notes
• Teaching tools

Course objectives

Introduction to Intelligent User Interfaces (IUIs) and their main features  that leverage  the symbiosis between humans and computers by merging two research fields: Artificial Intelligence (AI) and Human-Computer Interaction (HCI). This may involve including intelligent capabilities in the interface in order to improve performance, usability and experience in critical ways. It may also involve designing an interface that effectively leverages human skills and capabilities, so that human performance with an application improves.  IUIs  capabilities  have traditionally been associated more  with humans than with computers: how to perceive, interpret, learn, reason, plan, and decide.

Results of learning outcomes

At the end of the course students will have to demonstrate their ability to add intelligence to user interfacases in order to improve their capability and usability.

Course delivery

18  hours  of lesson in total (3 CFU), which take place in classroom with the help of projections. 

Learning assessment methods

Knowledge and skills  will be verified through an individual/group project  developed  and submitted according to given requisites 

Support activities

Seminars will be planned to deepen trend topics

Program

1. User and context modeling, semantic-based user model: an overview on the techniques for gathering  user data (interest, knowledge, emotional level, etc),  to infer user features from user behaviour, for creating and udpdating the user model; application on semantics on user modeling (Federica Cena)
2. Introduction to automated problem solving in knowledge based systems.  Managing knowledge, inference from knowledge. Introduction to the basic reasoning patterns and their application in intelligent user-adapted interaction (Luca Console)
3. Analysis of user input: emotion recognition through facial expressions, analysis of user gestures, brain wave analysis through Brain Computer Interfaces (BCI) (Cristina Gena)
4. Adaptive Output generation:  modalities to exploit the data in the user modeling for the generation of the  interfaces that are adaptive to user features,  examples of state of art adaptive systems and context aware systems (Federica Cena)
5.  Adaptive Output generation: Multimodal Interfaction with Gestural Interfaces and Social Robot  (Cristina Gena)

Slides of the course, available online on this web site.

Scientific articles will be also distributed to students regarding the topics discussed in class

Note

 The course will be held in September 2019: 

• venerdi 6 settembre: 10-13 sala riunioni
• martedi 10 settembre: 10-13  sala riunioni
• giovedi 12 settembre: 10-13  sala riunioni
• martedi 17 settembre: 10-13  sala riunioni
• giovedi 19 settembre: 10-13 aula D
• venerdi 20 settembre: 10-13 sala riunioni

• Teaching materials
• Exams and finals
• Go to Moodle
• Visit the forums