WAICA 2026 Workshop Call for PapersWAICA 2026 专题研讨会征稿
Workshop on Frontiers of Space-Based Intelligent Computing: Large Models, Agent Systems, and Space-Air-Ground Integration天基智能计算前沿研讨会：大模型、智能体系统与空天地一体化
Workshop Overview研讨会概述
Space-based intelligent computing represents a paradigm shift from ground-centric AI to distributed, autonomous intelligence leveraging satellite constellations, onboard processing, and space-air-ground integration. Key applications include Earth observation, global communications, disaster response, and environmental monitoring. However, space environments impose severe constraints: limited onboard resources, dynamic and unreliable network topologies, high latency, and adversarial security risks. While recent advances in edge intelligence, federated learning, foundation models, spatiotemporal learning, and AI-native communication offer potential solutions, bridging the gap between terrestrial AI techniques and space-hardened constraints remains an open challenge.天基智能计算正在推动从地面中心化 AI 向分布式、自主化智能范式转变，依托卫星星座、星上处理与空天地一体化能力，支撑地球观测、全球通信、灾害响应与环境监测等关键应用。然而，空间环境带来严苛约束：星上资源受限、网络拓扑动态且不稳定、高时延以及对抗安全风险。尽管边缘智能、联邦学习、基础模型、时空学习与 AI 原生通信等方向取得进展，但如何弥合地面 AI 技术与空间场景约束之间的鸿沟仍是开放挑战。
This workshop aims to bring together researchers and practitioners from academia and industry to exchange cutting-edge ideas, system architecture, and field deployments in space-based intelligent computing. We will identify core technical challenges, present recent breakthroughs, and chart future research directions across AI, aerospace, and communication engineering. Our goal is to accelerate the transition from ground-bound AI toward resilient, autonomous, and intelligent space-edge ecosystems.本研讨会旨在汇聚学术界与产业界研究者和实践者，共同交流天基智能计算领域的前沿思想、系统架构与实际部署经验。我们将识别核心技术挑战，展示最新突破，并探讨人工智能、航天与通信工程交叉方向的未来研究路线，推动从“地面绑定 AI”向“韧性、自主、智能的空间边缘生态”加速演进。
Topics of Interest征稿主题
We invite original contributions on topics including but not limited to:欢迎提交原创论文，主题包括但不限于：
- Edge intelligence and on-device learning for space systems面向空间系统的边缘智能与端侧学习
- Federated and distributed learning in non-IID space environments非独立同分布空间环境下的联邦与分布式学习
- Foundation models and large-scale AI for space data processing用于空间数据处理的基础模型与大规模 AI
- Spatiotemporal modeling and graph-based learning for satellite data卫星数据的时空建模与图学习
- Autonomous systems and self-evolving AI for space missions面向空间任务的自主系统与自演化 AI
- AI-native communication and computing co-designAI 原生通信与计算协同设计
- Large models (LLMs, LMMs) for Earth observation and space intelligence面向地球观测与空间智能的大模型（LLM/LMM）
- Agent-based space systems and multi-agent collaboration基于智能体的空间系统与多智能体协同
- Smart battery management and prediction for satellites卫星智能电池管理与预测
- Challenges in large-scale storage and retrieval of satellite images卫星图像大规模存储与检索挑战
- Security, robustness, and privacy in open space systems开放空间系统中的安全性、鲁棒性与隐私保护
- Real-world deployments and case studies of space-based AI天基 AI 的真实部署与案例研究
Submission and Review投稿与评审
WAICA incorporates a rigorous double-blind review process.WAICA 采用严格的双盲评审流程。
Papers that present data that include experiments on or with humans or animals and/or presentation or analysis of personally identifiable information, including aggregated data, must have obtained appropriate approval from the author(s)' institution(s). An explicit statement regarding such approval must be included in the paper. For submissions under double-blind review, all identifying information must be properly anonymized.凡涉及人类或动物实验数据，以及个人可识别信息（包括聚合数据）展示或分析的论文，须事先获得作者所在机构的相应审批，并在论文中明确说明。双盲评审投稿必须对所有身份信息进行规范匿名处理。
Workshop Organizers组织者
- Songwen Pei (Shanghai Institute of Technology) - General coordination裴松文（上海应用技术大学）- 总体统筹
- Kun Qiu (Fudan University) - Academic liaison, invited speakers仇堃（复旦大学）- 学术联络、邀请报告
- Yaoqi Liu (ComoSpace Company / ICT CAS) - Industry liaison, invited speakers刘耀奇（ComoSpace / 中国科学院计算技术研究所）- 产业联络、邀请报告
