About us

Q-Data 2026 is the 3rd workshop collocated with ACM SIGMOD/PODS 2026 that explores the potential of quantum computing and quantum-inspired hardware accelerators for data processing and data management. Topics of interest include enhancing database system components with quantum computing, hybrid quantum-classical data processing systems, quantum machine learning for autonomous database management, and domain-specific approaches for data analysis in sectors like finance or healthcare.

Important Dates

Fri, Mar 20, 2026
Paper submissions due
Sat, Apr 4, 2026
Notifications to authors
Fri, May 1, 2026
Camera-ready due
Sun, May 31, 2026
Workshop Date

Call For Paper

Quantum computing for data systems
Quantum computing for data exploration/discovery/integration
Quantum machine learning for databases
Databases for quantum computing
Enhancing database system components (e.g., query optimizer, query scheduler, transaction scheduler, authentication and integrity manager) with quantum computing and quantum-inspired accelerators
Data processing systems that integrate quantum-based and quantum-inspired accelerators, including hybrid quantum-classical approaches
Quantum machine learning for autonomous database management, database tuning, workload management, and learned indexes
Approaches for data exploration, discovery, and integration based on quantum computing and quantum-inspired hardware accelerators
Formal analysis and experimental evaluations assessing the potential of quantum computing for specific use cases in data processing and data management
Vision papers describing novel database system designs and novel use cases in data processing and management enabled by quantum computing
Quantum computing libraries and programming interfaces for database systems
Domain-specific approaches exploiting quantum computers and quantum-inspired accelerators for data analysis (e.g., in finance or health care)
Design of benchmarks, metrics, and evaluation frameworks for hybrid quantum–classical data processing systems and quantum-inspired accelerators
Leveraging ideas, techniques, and systems from the database community to support advances in quantum computing

We are allowing submissions for full, short, and abstract papers. The workshop explores the potential of quantum computing and quantum-inspired hardware accelerators for data processing and data management.

Committee

Workshop Chairs

Ibrahim Sabek

Workshop Chair

University of Southern California, USA

Immanuel Trummer

Workshop Chair

Cornell University, USA

Rihan Hai

Workshop Chair

TU Delft, Netherlands

Steering Committee

Jiaheng Lu

University of Helsinki, Finland

Le Gruenwald

University of Oklahoma, USA

Sven Groppe

University of LĂĽbeck, Germany

Wolfgang Mauerer

Technical University of Applied Sciences Regensburg, Germany