会議情報

TRUST 2027: ACM Conference on Trustworthy and Responsible AI and Computing Systems

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TRUST
投稿締切日:
2026-10-24 残り 105 日
通知日:
2026-12-31
開催日:
2027-03-07
開催地:
Washington DC, USA
閲覧: 29   フォロー: 0   参加: 0

論文募集

TRUST 2027 (ACM Conference on Trustworthy and Responsible AI and Computing Systems) is an academic conference held in Washington DC, USA on 2027-03-07. The paper submission deadline is 2026-10-24. Acceptance notifications are sent on 2026-12-31.

ACM TRUST 2027 welcomes original, unpublished research contributions that advance the design, verification, deployment, evaluation, and governance of trustworthy and responsible AI and computing systems. Scope Contributions may include new theories, algorithms, architectures, systems, benchmarks, evaluation frameworks, certification approaches, or deployment-oriented studies related to trustworthy and responsible AI and computing systems. Topics of Interest TRUST 2027 welcomes contributions across the following research areas. P1 Foundations of Trustworthy AI Formal verification of AI and ML systems Robustness, generalization, and adversarial resilience Interpretability and explainability foundations Uncertainty quantification and reliability metrics Causal reasoning and trustworthy inference Neuro-symbolic and hybrid AI approaches P2 Secure and Resilient AI Systems Adversarial machine learning Data poisoning and model backdoor defenses Secure model deployment pipelines Privacy-preserving AI and federated learning AI supply chain security Runtime monitoring and anomaly detection P3 Trustworthy AI in Systems and Infrastructure AI in cyber-physical systems Edge AI and trustworthy IoT Cloud and edge orchestration for safe AI AI reliability in distributed systems Trustworthy autonomous systems AI lifecycle management and MLOps assurance P4 Responsible AI, Governance and Compliance Fairness, bias mitigation, and accountability Transparency and auditability AI risk management frameworks Standards and certification of AI systems Ethical system design methodologies Benchmarking responsible AI practices P5 Evaluation, Benchmarking and Assurance Trustworthiness benchmarks Stress-testing frameworks Reproducibility and replicability in AI research Dataset integrity and data governance Risk assessment methodologies System-level validation and verification pipelines P6 Domain-Specific Trustworthy Applications Healthcare AI safety Smart grid and critical infrastructure Industrial AI and cyber-physical systems Financial AI risk control Public-sector AI systems Climate and sustainability systems
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関連ジャーナル

CCF正式名称インパクトファクター出版社ISSN
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems6.1Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
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BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536
AIEEE Transactions on Dependable and Secure Computing7.5IEEE1545-5971

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