Call for Workshop and Tutorial Proposals

Important dates

  • Discuss your topic with the Workshop and Tutorial Chairs - ASAP
  • Proposals due - 22 September 2021
  • Decisions sent - 13 October 2021

Tentative dates

  • Workshop submissions - 3 January 2022
  • Report workshop status to chairs - 10 January 2022
  • Go/No-go decision on workshops - 12 January 2022
  • Notifications to authors - 28 January 2022
  • Camera-ready for workshop summary - 9 February 2022
  • Camera-ready packages of accepted papers - 18 February 2022
  • Workshop held - 22 March 2022

Workshop and Tutorial Chairs

Alison Smith-Renner
Alison Smith-Renner
AI Group - Dataminr, USA
Ofra Amir
Ofra Amir
Technion - Israel Institute of Technology, Israel

Accepted Workshops

IUI 2022 is pleased to announce the following 8 workshops to be held in conjunction with the conference. The goal of the workshops is to provide a venue for presenting research on focused topics of interest and an informal forum to discuss research questions and challenges. Tutorials are designed to provide fundamental knowledge and experience on topics related to intelligent user interfaces, and the intersection between Human-Computer Interaction (HCI) and Artificial Intelligence (AI). Workshops and tutorials will be held on the first day of the conference.

Workshops with few submissions by Wednesday, 12 January 2022 may be cancelled, shortened, merged with other workshops, or otherwise restructured. The organizers of accepted workshops and tutorials are responsible for producing a call for participation and publicizing it, such as distributing the call to relevant newsgroups and electronic mailing lists, and especially to potential audiences from outside the IUI conference community. Workshop and tutorial organizers will maintain their own website with information about the workshop or tutorial and the IUI 2022 web site will refer to this website. The workshop organizers will coordinate the paper solicitation, collection, and review process. A workshop and tutorials summary will be included in the ACM Digital Library for IUI 2022, and we will separately publish a joint workshop proceedings for accepted workshop submissions (through CEUR or similar)

HUMANIZE: Transparency and Explainability in Adaptive Systems through User Modeling Grounded in Psychological Theory launch

Bruce Ferwerda
Jönköping University
Marko Tkalčič
University of Primorska
Panagiotis Germanakos

HUMANIZE aims to investigate how intelligent, adaptive systems can benefit from combining quantitative, data-driven approaches with qualitative, theory-driven approaches. We in particular invite work from researchers that incorporate features grounded in psychological theory (e.g. personality, cognitive styles etc.) into the predictive models underlying their adaptive/intelligent systems (e.g. recommender systems, website morphing, etc.). Apart from research investigating how this approach can improve these systems, we are interested in research towards the potential of this approach in improving explainability, fairness and transparency and reducing bias in data or output of intelligent systems.

APEx-UI: Adaptive and Personalised Explainable User Interfaces launch

Prof. Dr.-Ing. Ernesto William De Luca
Georg Eckert Institute
Pasquale Lops
University of Bari Aldo Moro
Cataldo Musto
University of Bari Aldo Moro
Erasmo Purificato
Otto von Guericke University Magdeburg

Adaptation and personalisation are crucial aspects of the design and development of successful artificial intelligence systems, from search engines and recommender systems to wearable devices. The increased desire for customisation inevitably leads to the need for the end-user to understand the rationale behind displaying that specific tailored content. The First Workshop on Adaptive and Personalised Explainable User Interfaces (APEx-UI 2022) aims to foster a cross-disciplinary and interdisciplinary discussion between experts from different fields (e.g. computer science, psychology, sociology, law, medicine, business, etc.) in order to answer a precise research question: "How can we adapt and personalise explainable user interfaces to the needs, demands and requirements of different end-users, considering their distinct knowledge, background and expertise?"

HAI-GEN: Human-AI Co-Creation with Generative Models launch

Justin D. Weisz
IBM Research AI
Mary Lou Maher
University of North Carolina
Hendrik Strobelt
IBM Research AI
Lydia Chilton
Columbia University
David Bau
Werner Geyer
IBM Research AI

Recent advances in generative AI through deep learning approaches such as generative adversarial networks (GANs), variational autoencoders (VAEs), and large language models will enable new kinds of user experiences around content creation, across a range of media types. These advances have enabled content to be produced with an unprecedented level of fidelity, for tasks such as generating faces, prose and poems, deep fake videos of celebrities, music, and even code. These examples also highlight some of the significant societal, ethical, and organizational challenges generative AI is posing. The goal of our workshop is to bring together researchers and practitioners from the domains of HCI & AI to establish a joint community to deepen our understanding of the human-AI co-creative process and to explore the opportunities and challenges of creating powerful user experiences with deep generative models.

Dyadic IMPRESSION Recognition Challenge launch

Chen Wang
University of Geneva
Guillaume Chanel
University of Geneva
Beatrice Biancardi
LTCI, Télécom Paris
Chloé Clavel
LTCI, Télécom Paris

The Dyadic IMPRESSION Recognition Challenge, to be held in March 2022 in conjunction with IUI 2022 in Helsinki, Finland, will be devoted to all aspects of artificial intelligence and behavioral science for the analysis of human-human interaction from multimodal data. To advance and motivate the research on human bodily responses in dyadic interactions, we organize the challenge which uses the open and accessible multimodal IMPRESSION dataset. It addresses multimodal recognition as well as dynamic multi-user recognition, where both interlocutors’ information can be exploited.

HEALTHI: Intelligent Healthy User Interfaces launch

Katrin Hänsel
Yale University
Michael Sobolev
Cornell Tech
Assistant Professor Tobias Kowatsch
ETH Zurich
Rafael A Calvo
Imperial College London

This second multidisciplinary workshop on Healthy Interfaces (HEALTHI) offers a forum that brings academics and industry researchers together and seeks submissions broadly related to the design of smart user interfaces for promoting health. It builds on the fields of psychology, behavioral health, human computer interaction, ubiquitous computing, and artificial intelligence. The workshop will discuss intelligent user interfaces such as screens, wearables, voices assistants, and chatbots in the context of accessibly and fairly supporting health, health behavior, and wellbeing.

TExSS: Transparency and Explanations in Smart Systems launch

Tsvi Kuflik
The University of Haifa
Jonathan Dodge
Oregon State University
Dr. Styliani Kleanthous Loizou
Open University of Cyprus
Brian Y Lim
National University of Singapore
Carina Negreanu
Microsoft Research
Avital Shulner-Tal
The University of Haifa
Dr. Simone Stumpf
City, University of London
Dr. Min Kyung Lee
University of Texas at Austin
Dr. Advait Sarkar
Microsoft Research
Dr. Alison Smith-Renner
AI Group, Dataminr

Smart systems, such as decision support or recommender systems, continue to prove challenging for people to understand, but are nonetheless ever more pervasive based on the promise of harnessing rich data sources that are becoming available in every domain. These systems tend to be opaque, raising important concerns about how to discover and account for fairness or bias issues. The workshop on Transparency and Explanations in Smart Systems (TExSS) welcomes researchers and practitioners interested in exchanging ideas for overcoming the design, development, and evaluation issues in intelligent user interfaces. Specifically, we will focus on barriers preventing better reliability, trainability, usability, trustworthiness, fairness, accountability, and transparency. This year’s theme is “Responsible, Explainable AI for Inclusivity and Trust”, emphasizing the importance of responsibility that tech-industry and developers have towards the design, implementation and evaluation of explainable, inclusive and trustworthy human-AI interaction.

ESIDA: Exploratory Search and Interactive Data Analytics launch

Dorota Glowacka
University of Helsinki
Evangelos Milios
Dalhousie University
Axel J. Soto
Fernando V. Paulovich
Dalhousie University
Osnat (Ossi) Mokryn
University of Haifa

The aim of this workshop is to explore new methods and interface/system design for interactive data analytics and management in various domains, including specialised text collections (e.g. legal, medical, scientific), multimedia, and bioinformatics, as well as for various tasks, such as semantic information retrieval, conceptual organization and clustering of data collections for sense making, semantic expert profiling, and document/multimedia recommender systems. The primary audience of the workshop are researchers and practitioners in the area of interactive and personalised system design as well as interactive machine learning both from academia and industry.

SOCIALIZE: SOcial and Cultural IntegrAtion with PersonaLIZEd Interfaces launch

Fabio Gasparetti
Roma Tre University
Cristina Gena
University of Torino
Giuseppe Sansonetti
Roma Tre University
Marko Tkalčič
University of Primorska

The SOCIALIZE workshop aims to bring together all those interested in the development of interactive techniques that may contribute to foster the social and cultural inclusion of a broad range of users. More specifically, we intend to attract research that takes into account the interaction peculiarities typical of different realities, with a focus on disadvantaged and at-risk categories (e.g., refugees and migrants) and vulnerable groups (e.g., children, elderly, autistic and disabled people). Among others, we are also interested in human-robot interaction techniques aimed at the development of social robots, that is, autonomous robots that interact with people by engaging in social-affective behaviors, abilities, and rules related to their collaborative role.