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Challenges and Future Trends of Human–Computer Interaction

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 November 2026 | Viewed by 729

Editors

Special Issue Information

Dear Colleagues,

Human–Computer Interaction (HCI) is an interdisciplinary field that examines how people engage with digital technologies across diverse contexts. It considers cognitive, social, and experiential aspects of interaction, focusing on how users communicate, work, and live with computing systems across a wide range of digital and physical environments.  

As technology continues to evolve, HCI research increasingly focuses on designing interactive systems that are intelligent, adaptive, and embedded in everyday environments. In particular, advances in Artificial Intelligence are reshaping HCI by influencing theoretical frameworks, improving data-driven methods for understanding user behavior, and enabling new forms of interaction and system design. These developments support more personalized and context-aware experiences, while also transforming how users engage with digital systems. At the same time, emerging autonomous and embodied technologies are redefining human–technology relationships across various domains. Across these changes, accessibility and inclusivity remain central to ensuring that systems are usable and beneficial for diverse user populations.

Research areas relevant to the journal include:

  • Human–AI Interaction: Intelligent, adaptive, and proactive interactive systems.
  • Multimodal Interaction: Seamless integration of speech, gesture, gaze, and haptic-based interfaces.
  • Data-Driven HCI: AI-powered methodologies, predictive modeling, and data-informed user analytics.
  • Emerging Interaction Frontiers: Human–robot interaction, autonomous systems, and immersive XR (AR/VR/MR) experiences.
  • Inclusive Design: Digital accessibility, universal design, and social inclusivity in interactive systems.
  • Cognitive UX: Psychological, emotional, and ergonomic aspects of intelligent and adaptive environments.

Dr. Hyun K. Kim
Dr. Jaehyun Park
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • human-AI interaction
  • multimodal interaction
  • data-driven HCI
  • VR/AR/XR
  • human-robot interaction
  • autonomous vehicle
  • inclusive design
  • accessibility

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Published Papers (1 paper)

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Research

16 pages, 19646 KB  
Article
Predicting User-Preferred Ventilated Seat Intensity in a Dynamic Cooling Environment: A Pilot Study for Adaptive Smart Vehicle Seats
by Jangwoon Park, Ian D. Garcia, Kang Yen Lee and Baekhee Lee
Appl. Sci. 2026, 16(13), 6595; https://doi.org/10.3390/app16136595 - 2 Jul 2026
Viewed by 335
Abstract
This pilot study investigated user-preferred ventilated seat intensity levels under simulated hot vehicle cabin cooling conditions to support adaptive seat ventilation systems. Thirty-three participants were exposed to a transient cooling environment in which cabin temperature decreased from approximately 38 °C to 25 °C [...] Read more.
This pilot study investigated user-preferred ventilated seat intensity levels under simulated hot vehicle cabin cooling conditions to support adaptive seat ventilation systems. Thirty-three participants were exposed to a transient cooling environment in which cabin temperature decreased from approximately 38 °C to 25 °C following air-conditioning activation. Participants selected preferred seat ventilation intensity levels (Low, Medium, or High) while demographic and environmental variables were evaluated. Results indicated that cabin temperature was the strongest predictor of ventilation intensity preference, followed by elapsed cooling time and relative humidity. Age demonstrated a statistically significant effect, whereas height, body weight, BMI, and sex were not statistically significant predictors. An exploratory multinomial logistic regression model demonstrated preliminary predictive feasibility with a cross-validated classification accuracy of 73.2%. The findings suggest that occupant-preferred ventilation intensity levels may be estimated using demographic and environmental variables under transient vehicle cooling conditions. Full article
(This article belongs to the Special Issue Challenges and Future Trends of Human–Computer Interaction)
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