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Adaptive User Interfaces through Machine Learning
Last Updated: 2026-06-03 00:14:20
Abstract
In the recent years, there have been major technological advances in commercial virtual and augmented reality systems. Those advancements lead to many open challenges in terms of perception and interaction as well as technical challenges. In this course, students present and discuss papers from relevant top-tier research venues to extract techniques and insights from MR research.
Objective
The objective of the seminar is for participants to collectively learn about the state-of-the-art research in Mixed Reality (primarily augmented and virtual reality) and closely related areas. This includes the ability to concisely present results of pioneering as well as state-of-the-art research. Another objective is to collectively discuss open issues in the field and developing a feeling for what constitutes research questions and outcomes in the field of technical Human-Computer Interaction.
Content
The seminar format is as follows: attendees individually read one full-paper publication, working through its content in detail and possibly covering some of the background if necessary, and present the approach, methodology, research question and implementation as well as the evaluation and discussion in a 20–25 min talk in front of the others. Each presenter will then lead a short discussion about the paper, which is also guided by questions posed to the audience.
Resources
Literature
18 papers will be provided by the lecturer and distributed in the first seminar on a first-come, first-served basis according to participants' preferences. The lecturer will also give a brief run-down across all 18 papers in a fast-forward style, covering each paper in a single-minute presentation, and outline the difficulties of each project. The schedule is fixed throughout the term with easier papers being presented earlier and more comprehensive papers presented later in the term.
Learning Materials (Links)
General Information
- Language
- English
- Levels
- BSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Registration & Places
- Max Places
- 18
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| seminar | Adaptive User Interfaces through Machine Learning |
|
2 h weekly |
Offered In
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Electives (This is only a short selection. Other courses from the ETH course catalogue may be chosen. Please consult the "Richtlinien zu Projekten, Praktika, Seminare" (German only), .)
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