特别分会 1:

Responsible Quantum/Classical AI for Trustworthy and Scalable Real-world Systems

分会主席：
Prof. Youyang Qu, Data61, CSIRO, Australia
Dr. Jun Bai, Mcgil University, Australia
Dr. Keshav Sood, Deakin University, Australia
Prof. Longxiang Gao, Qilu University of Technology, China

议题:
Recent advances in artificial intelligence have increasingly emphasized responsibility, trustworthiness, and scalability in real-world deployment. As AI systems transition from classical paradigms to quantum-enhanced models, ensuring ethical, secure, and explainable intelligence becomes both more challenging and more critical. This special session aims to bring together researchers and practitioners from academia, industry, and government to explore emerging methods, frameworks, and applications of responsible Quantum/Classical AI.
The session will focus on cross-disciplinary innovations that combine ethical design principles, trustworthy learning algorithms, and scalable computing architectures for practical deployment across domains such as cybersecurity, energy systems, healthcare, finance, and intelligent manufacturing. It will serve as a forum for discussing both theoretical foundations and real-world implementation challenges, including governance, interpretability, and robustness of hybrid AI systems.
Topics of interest include (but are not limited to):
 Trustworthy and explainable AI models in classical and quantum domains
 Ethical governance frameworks for hybrid Quantum/Classical intelligence
 Scalable quantum machine learning and federated AI architectures
 Privacy-preserving and secure AI computation at scale
 Responsible data management and unlearning in hybrid AI environments
 Quantum-enhanced optimization for sustainable and ethical applications
 Evaluation metrics and benchmarks for trustworthy hybrid AI
 Real-world deployment case studies in energy, cybersecurity, and healthcare

分会投稿流程:

如果您希望参加RQATSRS特别分会，请将您的稿件通过 ConfSync:https://confsync.cn/csae/submission系统提交，并在投稿时选择Session：“Responsible Quantum/Classical AI for Trustworthy and Scalable Real-world Systems”。我们会将您的投稿分配给Prof.Youyang Qu进行初审，初审通过之后将安排专家进行二审，稿件录用通知发放时间与主会议通知时间一致。有任何问题可以联系：info@confsync.cn 。