Affective Computing in Cloud-Edge Environments

Special Section at CloudCom 2025

Special Section Overview

Affective Computing, as a core technology of Human-Computer Interaction (HCI) and intelligent services, is rapidly transitioning from the laboratory to the real world at an unprecedented pace, profoundly reshaping and enabling the ubiquitous deployment of numerous critical fields. Its essence lies in endowing machines with the capability to recognize, understand, process, and simulate human emotions, thereby constructing more empathetic, adaptive, and natural interactive experiences. This technology has deeply penetrated key cloud-driven application scenarios such as mental health services (e.g., assisted diagnosis of mood disorders, AI-powered psychological companionship), immersive entertainment (e.g., emotion-driven content generation in VR/AR, emotional responses of game characters), and intelligent education (e.g., learning emotion analysis, personalized tutoring). It has become a key driver in enhancing service intelligence and user experience.

However, with the explosive growth of multi-modal affective data (physiological signals, behavioral data) on edge devices, Affective Computing faces significant challenges including high privacy sensitivity, high computational heterogeneity, and weak adaptability to dynamic environments. Traditional centralized affective analysis frameworks struggle to meet the requirements for real-time processing, user privacy protection, and collaboration among resource-constrained edge devices.

This special session aims to focus on the critical direction of cloud-edge-device collaborative architecture, exploring novel paradigms urgently needed for the ubiquitous deployment of Affective Computing. We solicit prospective and practical research contributions.

Topics of Interest

We invite high-quality, original research submissions on topics including, but not limited to:

  • Acquisition and Fusion of Multimodal Affective Signals (Physiological Signals, Behavioral Data)
  • Federated Learning for Physiological Signals and Behavioral Data Acquired from Ubiquitous Edge Devices (e.g., Wearable Sensors, Smartphones)
  • Generalization Capability of Affective Computing Models for Universalized Scenarios (e.g., Adaptation to Cross-Cultural, Cross-Age, and Cross-Individual Differences)
  • Ethics and Fairness in Affective Computing
  • Secure Handling of Privacy-Sensitive and Highly Personalized Affective Data
  • Dynamic Environment Adaptability (e.g., How to Ensure Model Robustness in Scenarios like Cross-Domain?)
  • Multimodal Fusion with Low-Quality Data (e.g., Data Missing, Poor Data Quality)
  • Building Trustworthy Affective AI
  • Human-Computer Interaction in Cloud-Edge Collaboration
  • Trustworthy Affective Computing Models in Cloud-Edge Collaborative Environments

Important Dates

  • Paper Submission: September 6, 2025
  • Notification of Acceptance: October 4, 2025
  • Camera-Ready: October 30, 2025
  • Special Section Date: November 16, 2025 (TBC)

Submission Guidelines

Authors are invited to submit original, unpublished research papers. Submissions should not exceed 8 pages, including tables, figures, and references in IEEE CS format. The template files for LATEX or WORD can be downloaded from the IEEE site https://www.ieee.org/conferences/publishing/templates.html. Submission must be made in PDF format only with savable text and embedded fonts.

The review process will be doubly blind, and so a submission should not include any information that may identify the authors of the manuscripts. Technical content of the camera-ready manuscript must be identical to the submitted version except for changes made to address TPC review comments.

For each accepted submission, at least one of the co-authors must have a full conference registration and present the work in person.

Special Section Chairs (alphabetical order)

  • Chengsheng Mao, Northwestern University, USA (chengsheng.mao@northwestern.edu)
  • Minqiang Yang, Lanzhou University, China (yangmq@lzu.edu.cn)
  • Ricardo Jorge da Silva Santos, Polytechnic of Porto, Portugal (rjs@estg.ipp.pt)
  • Rui Liu, Inner Mongolia University, China (imucslr@imu.edu.cn)
  • Yongfeng Tao, Lanzhou University, China (taoyongfeng@lzu.edu.cn)
  • Yuan Zong, Southeast University, China (xhzongyuan@seu.edu.cn)

Contact Information

For any inquiries about the section, please contact:

Email: taoyongfeng@lzu.edu.cn

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