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Fri, 13 Dec 2019 12:22:30 +0200
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Kashyap Todi <[log in to unmask]>
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AI4AUI: IUI 2020 Workshop on AI Methods for Adaptive User Interfaces

CALL FOR POSITION PAPERS

Submission Deadline: December 20, 2019
Workshop Date: 17 March, 2020
Location: ACM IUI 2020 – Cagliari, Italy
Website: ai4aui.wordpress.com <http://ai4aui.wordpress.com/>
Submission Link: https://easychair.org/conferences/?conf=ai4aui <https://easychair.org/conferences/?conf=ai4aui>
Contact: [log in to unmask] <mailto:[log in to unmask]>

TL;DR: During this hands-on workshop at IUI 2020, we will discuss, explore, and apply AI methods towards future adaptive user interfaces to improve aspects such as usability and aesthetics. You are invited to submit a short position paper on relevant topics by 20th December 2019. Selected papers will be discussed at the workshop (on 17 March , 2020), where at least one of the author’s is required to register and participate.

Introduction: An adaptive user interface (AUI) can modify or change its layout, behaviour, and content based on the user, such as their abilities or intents, and their context of use, such as their platform or environment. Artificial Intelligence (AI) is a powerful tool for learning from data, to make inferences and plan actions that can drive a system towards a preferred state. This workshop aims to investigate how we can apply AI methods towards future AUIs. More specifically, using a hands-on approach, we will explore the application of AI and Machine Learning (ML) towards objectively improving aspects such as usability, reliability, and aesthetics while adapting UIs. 

Workshop Overview: Participants will briefly present a case study, based on prior or upcoming research, and classify their proposed technique in terms of several criteria, such as (but not limited to): input, technique, output, adaptation steps covered, adaptation time, level of automation, software quality properties addressed, measurement method, potential benefits, and drawbacks. During the workshop, we will cluster these for group discussions according to the aforementioned criteria, such as by technique family or property addressed. We will then break out into focus groups, to work on key identified themes. Through brainstorming and prototyping, we will explore the application of AI methods towards improving AUIs. From these discussions, an AI4AUI framework will emerge that will be used for positioning, comparing presented techniques, and for generating future avenues.

Call for Participation: We encourage you to submit a short position paper in any suitable format. No particular template is enforced, but please use legible fonts and maintain the length within 4 pages (A4 size). All papers will be refereed, single blind (i.e. author names and affiliations should be listed). If accepted, at least one of the authors must register and attend the workshop. A workshop summary will be included in the ACM Digital Library for IUI 2020, and a detailed description of the results will be included on this page (with permission from participants). Position papers are not included within the ACM IUI Proceedings, but we will consider publishing them through CEUR Workshop Proceedings. Encouraged topics related to the theme of the workshop include, but are not limited to:
• Novel adaptive UIs
• AI methods for personalisation, customisation, etc.
• Interaction techniques for AUIs
• Mixed-initiative UI adaptations
• New methods for capturing data about users and context, and making inferences
• Computational models and algorithms for AUIs

Please submit your position paper to EasyChair by 20 December, 2019 at:
https://easychair.org/conferences/?conf=ai4aui <https://easychair.org/conferences/?conf=ai4aui>.

Organisers
• Kashyap Todi – Aalto University
• Jean Vanderdonckt – Universite catholique de Louvain, LouRIM
• Xiaojuan Ma – Hong Kong University of Science and Technology
• Jeff Nichols – Google LLC
• Nikola Banovic – University of Michigan

Please feel free to contact us for more information or questions at: [log in to unmask] <mailto:[log in to unmask]>.
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