International Workshop on Reliable Data-Driven Intelligence (RDDI 2027)

Description

Data-driven intelligence is a core branch of artificial intelligence research and industrial deployment. Beyond basic data analysis and intelligent inference capabilities, reliability, robustness, and dependability stand as critical requirements for data-driven intelligent systems, especially when deployed in high-stakes, mission-critical, and safety-related application scenarios.

This workshop aims to share diverse applications, methodologies, and technical frameworks for reliable data-driven intelligence, model and quantify the reliability metrics and performance requirements of data-centric AI systems, and exchange innovative ideas between academic researchers and industrial practitioners to advance the development of trustworthy, stable, and verifiable data-driven intelligence. The workshop welcomes papers and presentations in the field of data mining, machine learning, deep learning, large language model applications, system reliability modeling, robustness optimization, and practical data-driven intelligent systems.

Topics

The list of topics includes, but is not limited to:

• Reliable data-driven modeling and optimization
• Trustworthy big data analytics and inference
• LLM-based reliable data interpretation and mining
• Data-centric AI robustness and vulnerability assessment
• Dependability verification for data-driven intelligent systems
• Uncertainty quantification in data-driven prediction
• Reliability metrics and evaluation for data intelligence
• Privacy-preserving reliable data analysis
• Fault detection and diagnosis in data-driven pipelines
• Data quality enhancement for dependable AI systems
• Formal validation of data-driven decision frameworks
• Industrial empirical studies for reliable data intelligence
• Performance and redundancy analysis of data-centric systems
• Prognostics via reliable data-driven techniques
• Tools and benchmarking for dependable data analytics

Submission

Authors are invited to submit original unpublished research papers as well as industrial practice papers. Simultaneous submissions to other conferences are not permitted.

Papers should be written in English and submitted in PDF format. The length of a camera ready paper will be limited to ten pages, including the title of the paper, the name and affiliation of each author, a 150-word abstract, and up to 6 keywords. Shorter version papers (up to four pages) are also allowed.

Authors must follow the ISSSR conference proceedings format (PDF | Word DOCX | Latex) and Submission Guidelines to prepare their papers. Each submission will be reviewed by at least three program committee members. Paper selection is based on originality, technical contribution, presentation quality, and relevance to the workshop.

At least one of the authors of each accepted paper is required to pay a full registration fee and present the paper at the workshop. Authors of top-quality papers will be invited to submit their extended versions to special issues of selected SCI journals.

Program Chairs

Mingwei Tang China

Nanjing Audit University, China

Yi Zhu China

Nanjing Audit University, China

Program Committee