Lecture Introduction to Intelligent User Interfaces
Lecturer: Prof. Dr. Andreas Butz, Prof. Dr. Albrecht Schmidt, Prof. Dr. Sven MayerTutorials: Luke Haliburton, Jesse Grootjen
Hours per week: 2 (Lecture) + 2 (Tutorial)
ECTS credits: 6
Language: English
Module: Vertiefende Themen für Master Medieninformatik, Informatik und MCI
Capacity: max. 50
News
- 01.02.2022: The final presentations will take place online.
- 19.08.2021: Given the current situation on how we are allowed to run in-person lectures at least parts of the lecture if not all are very likely to be held in person.
- 19.07.2021: This page is still under development, all content may be subject to change.
Dates and Locations
-
Lecture:
Date: Thu, 12-14 c.t.
Location: Geschw.-Scholl-Pl. 1 (M), M 101 - alternativly, via Zoom (interactive live sessions)
First session: October 21, 2021 -
Tutorial:
Date: Mon, 16-18
Location: Amalienstr. 73A, Room: 220 - alternativly, via Zoom (interactive live sessions)
First session: October 25, 2021
The course (lecture and exercise) is offered in-person this semester. All in-person lectures will be interactive sessions. Interactive sessions are not recorded but are transmitted in online via Zoom, so that remote participation is sufficient for the entire semester.
Contents
The module Intelligent User Interfaces (IUI) looks at current topics within the intersection of human computer interaction and machine learning. The course focuses on the adaptation of techniques originating from machine learning and artificial intelligence for practical applications within the research area of human computer interaction. Topics include (tentative):- Voice User Interfaces
- Natural Language Processing
- Recommender Systems
- Explainability of Intelligent Systems
- Physiologically-Based Interfaces
- ...
Students are expected to create their own intelligent system (in groups of four) over the course of the semester and present intermediate milestones throughout the tutorials. These include short concept presentations: explain how a new aspect as presented in the lecture integrates into your system; and milestone presentations a week later that showcase the implementation. This cycle repeats bi-weekly. Tutorials will also be used to introduce lecture topics in the form of hands-on exercises.
Tasks
- Attend all classroom events (lectures AND tutorials)
- Presentation of concepts and milestones for the project
- Final project presentation
- Project contribution statement (who in the group did what)
- Exam
Requirements
- Human Computer Interaction
- Machine Learning, e.g. Pratical Machine Learning
Lectures
All in-person sessions will be discussion sessions and additional content beyond the recordings will be provided. In-person sessions will not be recorded but only streamed (slides will be provided). Recordings will not be played back in the in-person session but have to be watch upfront.
| Date | Location | Topic | Recording for this Topic |
|---|---|---|---|
| 21.10. | In person | Introduction to Intelligent User Interfaces | |
| 28.10. | In person | Discussion Artificial Intelligence | Lecture 02 |
| 11.11. | In person | Discussion Deceptive User Interfaces & Voice UI | Lecture 03 Lecture 04 |
| 25.11. | In person | Discussion Intelligent Text Entry | Lecture 05 |
| 02.12. | In person | Discussion Text and Natural Language Processing | Lecture 06 |
| 09.12. | In person | Discussion Context Awareness Interaction in Smart Environments | Lecture 07 |
| 20.01. | Only Online | Discussion Recommender Systems | Lecture 08 Lecture 09 Lecture 10 Lecture 11 |
| 03.02. | Only Online |
Discussion Explainable AI, Bias and Ethics, and Q&A | Lecture 12 Lecture 13 |
| 10.02. | Only Online |
Final Presentations | Lecture 14 |
Exercises
In-person tutorial sessions will not be recorded but only streamed (slides will be provided).
The exercises include different formats: (1) Live coding sessions in which the lecture content is applied in practice, (2) Project pitches in which students present the current status of their project and receive feedback.
Please note that the following exercise syllabus is tentative and subject to change over the course of the semester.
Dates with mandatory attendance are marked with an "*".
| Date | Topic |
|---|---|
| Oct 25 * | Organization, Live Coding Session: Introduction to Python and ML |
| Nov 08 | Live Coding Session |
| Nov 15 * | Project Ideation + Q&A |
| Nov 22 * | 1min Project Pitches + Live Coding Session |
| Nov 29 | Live Coding Session + Individual Help for Projects if Needed |
| Dec 06 * | 3min Project Pitches: Show Current Project Status |
| Dec 13 | Live Coding Session + Individual Help for Projects if Needed |
| Jan 10 * | 5min Project Report: Show Current Project Status |
| Jan 17 | Individual Help for Projects if Needed |
| Jan 24 | Introduction to Giving Great Project Presentations, Individual Help for Projects |
| Jan 31 | Individual Help for Projects if Needed |
| Feb 07 | Q&A: Exam preparation |
Exam
The exam will consist of two parts:
- Your practical project including the final presentation (1/2 of the final grade)
- An Exam about the content of the lectures and exercises (1/2 of the final grade)
(Written exam if possible, otherwise (online) oral)
Please find the dates for the exams here:
- tbd.
- tbd.
