The 1st Workshop on Quantum Machine Learning (QML 2026)
Call for Papers
Quantum computing has rapidly evolved, progressing from theoretical foundations in the 1980s to current hardware capable of managing hundreds of qubits. While still in its early stages, advances in noisy intermediate-scale quantum (NISQ) devices show promise in outperforming classical systems in specific applications, including quantum machine learning (QML), variational quantum algorithms (VQAs), and Hamiltonian simulations.
This workshop aims to bring together experts to discuss integrating quantum computing with communication networks and machine learning. Topics will include quantum communication protocols, quantum network optimization, and quantum-enhanced machine learning, showcasing how quantum technologies can transform these fields.
We invite submissions on topics related to the utilization of quantum computing, QML, and quantum communications to enhance the performance and optimize the design and operation of next-generation communication networks and machine learning systems. Topics include (but are not limited to):
This workshop aims to bring together experts to discuss integrating quantum computing with communication networks and machine learning. Topics will include quantum communication protocols, quantum network optimization, and quantum-enhanced machine learning, showcasing how quantum technologies can transform these fields.
We invite submissions on topics related to the utilization of quantum computing, QML, and quantum communications to enhance the performance and optimize the design and operation of next-generation communication networks and machine learning systems. Topics include (but are not limited to):
- QML theory and applications
- QML for 6G security
- Quantum optimization for resource allocation in wireless communication networks
- Case studies and implementations of QML in various applications
- QML for IoT and edge computing
- Quantum communications and QML for autonomous mobility
- Quantum federated learning and split learning
- Quantum reinforcement learning and entanglement distribution for distributed systems
Important Dates
- Paper Submission Deadline: Sept. 26, 2025
- Notification of Acceptance: Nov. 15, 2025
- Camera Ready Deadline: Dec. 5, 2025
- Conference Dates: Jan. 14-16, 2026
Workshop Chair
- Joongheon Kim (Korea University)
Workshop Organizer
- Soyi Jung (Ajou University)
- Soohyun Park (Sookmyung Women’s University)
- Youn Kyu Lee (Chung-Ang University)
Authors are invited to submit full paper (5~6 pages) or short paper (3~4 pages) electronically as PDF files through EDAS. Details about the submission process including formatting instructions will be available at the conference website, https://www.icoin.org.
Technical Co-sponsors
- Net-Zero CAFE (Connectivity and Autonomy for Future Ecosystem) Research Center (funded by IITP), Korea University