Conference Information
IUI 2021: International Conference on Intelligent User Interfaces
Submission Date:
Notification Date:
Conference Date:
College Station, Texas, USA
CCF: b   CORE: a   QUALIS: a1   Viewed: 13317   Tracked: 38   Attend: 6

Conference Location
Call For Papers
ACM IUI 2021 is the 26th annual premier international forum for reporting outstanding research and development on intelligent user interfaces.

ACM IUI is where the Human-Computer Interaction (HCI) and Artificial Intelligence (AI) communities meet, with contributions from related fields such as psychology, behavioral science, cognitive science, computer graphics, design, the arts, and more. Our focus is on improving the interaction between humans and digital technology, by leveraging both HCI approaches and state-of-the art AI techniques from machine learning, natural language processing, data mining, knowledge representation and reasoning.

Why you should submit to ACM IUI

While other conferences focus on either the AI or HCI side of this research, we address the complex interaction between the two. We strongly encourage submissions that simultaneously discuss research from both HCI and AI. We also welcome works that focus more on one side or the other, but still highlight the connections between the two. We value papers that contribute methodology or theory for the evaluation of intelligent user interfaces. We do not require evaluations with users, but we do expect papers to include an appropriate evaluation for their stated contributions.

ACM IUI welcomes contributions from all relevant arenas—academia, industry, government, and non-profit organizations—and gives its participants the opportunity to present and see cutting-edge IUI work in a focused and interactive setting. The conference is large enough to be diverse and lively, but small enough to allow for extensive interaction among attendees and easy attendance to the events that the conference offers, ranging from oral paper presentations, poster sessions, workshops, panels and a doctoral consortium for graduate students.


We invite original paper submissions that describe novel user interfaces, applications, interactive and intelligent technologies, empirical studies, or design techniques. We do not require evaluations with users, but we do expect papers to include an appropriate evaluation for their stated contribution.

Accepted papers will appear in the ACM Digital Library and citation indices. A selected set of accepted top quality full papers will be invited to submit their extended versions for publication in an ACM Transactions on Interactive Intelligent Systems (TiiS, special issue titled "Highlights of IUI 2021".


IUI topics of interest include, but are not limited to:

Application areas

    Internet of Things (IoT)
    Education and learning-related technologies
    Health and intelligent health technologies
    Assistive technologies
    Social media and other Web technologies
    Mobile applications
    Artificial personal assistants
    Information retrieval, search, and recommendation system

Interface types

    Affective and aesthetic interfaces
    Collaborative interfaces
    Speech-based interfaces
    AR/VR interfaces
    Intelligent wearable and mobile interfaces
    Ubiquitous smart environments


    Agent based interfaces (e.g., embodied agents, virtual assistants)
    Multi-modal interfaces (speech, gestures, eye gaze, face, physiological information, etc.)
    Conversational interfaces
    Tangible interfaces
    Intelligent visualization

Methods and approaches

    Methods for explanations (e.g., transparency, control, and trust)
    Persuasive technologies in IUI
    Privacy and security of IUI
    Planning and plan recognition for IUI
    Knowledge-based approaches to user interface design and generation
    User Modelling for Intelligent Interfaces
    User-Adaptive interaction and personalization
    Crowd computing and human computation
    Human-in-the loop machine learning

Evaluations of intelligent user interfaces

    User experiments
    User studies
    Reproducibility (including benchmarks, datasets, and challenges)
    Mixed-methods evaluations
Last updated by Dou Sun in 2020-07-30
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