Seminar WS 21/22:
Computing the User (and their interface)
At the core of many intelligent systems are computational models of the user. They are used to predict users’ behavior, their perception of an interface, their intention or interests, and many more. This seminar will introduce students to how such models are developed using computational methods.
Every week we will hear about state-of-the-art research that applies methods from machine learning, optimization, bayesian theory, or other fields to develop predictive or descriptive user models. We will learn how these are applied to improve the user’s interaction with a computing system or to enable entirely new ways to interact. In discussing these research papers, students will take on different roles, acting as presenter, historian, journalist or PhD student (see below). As such, the seminar teaches basic scientific writing and oral presentation skills. The different roles encourage more discussion and a deeper learning experience.
Each week, students will take on a different role with respect to the discussed paper. In brief, these are:
- Presenter: Give a short presentation about the paper that you read in depth.
- Historian: Find out how this paper sits in the context of the related work. Use bibliography tools to find the most influential papers cited by this work and at least one paper influenced by the work. In a short presentation, briefly discuss these papers and the broader areas of related work.
- PhD student: Propose (in written form) a follow-up project for your own research based on this paper – importantly the project should be directly inspired by the paper or even use/extend the method proposed.
- Journalist: After the presentation, write an article about the the paper that can be understood by the general public; include points from the general discussion during the seminar, the historian, or the PhD student.
- All students (every week): Post three discussion points before each session.
Attendance in the weekly meetings is mandatory.