# COAC — International Conference on Optics for AI Clusters

- **Submission deadline**: 2026-10-15
- **Notification date**: 2026-10-31
- **Conference date**: 2026-12-13
- **Location**: Hefei, China
- **Trackers**: 0
- **Attendees**: 0
- **Canonical page**: https://www.myhuiban.com/conference/5899

## Call for papers

Scope and Topics We solicit original, high-quality research papers and practical experience reports on all aspects of optics for AI clusters. Topics of interest include, but are not limited to: Optical Interconnect Architectures for AI Clusters Optical interconnect for scale-up domains and scale-out fabrics in AI clusters Co-packaged optics, near-packaged optics, and on-board optical engines Optical input/output and chip-to-chip photonic links for accelerators and memory Hybrid electrical-optical topologies, network design, and cluster-level case studies Optical Switching and Network Fabrics Optical circuit switching, wavelength routing, and reconfigurable optical fabrics Optical packet and burst switching for bursty AI training traffic All-to-all, collective communication, and in-network computing over optical fabrics Control planes, scheduling, and fast reconfiguration for optical AI networks Optical Transceivers, Links, and Physical Layer Technologies High-speed optical transceivers, intensity-modulation and coherent-lite architectures Linear-drive, low-power optics and the removal of retimers and DSP in short-reach links Modulation formats, forward error correction, and digital signal processing for AI links Link budget, signal integrity, and physical-layer measurement of optical AI interconnects Optical Devices, Photonic Integration, and Packaging Silicon photonics, silicon nitride, thin-film lithium niobate, and heterogeneous integration Lasers, modulators, photodetectors, and wavelength-division multiplexing components Optical packaging, fiber coupling, co-design with electronic dies, and thermal packaging Optical I/O chiplets, photonic interposers, and advanced interconnect packaging Photonic Computing and Optical Acceleration Photonic tensor cores, optical matrix multiplication, and analog optical computing Optical neural networks and photonic inference accelerators Non-von Neumann and neuromorphic photonic architectures for AI workloads Integration of photonic accelerators with electronic AI systems and software stacks Energy Efficiency, Thermal Management, and Reliability Power and energy modeling of optical interconnects versus electrical alternatives Thermal management, wavelength drift control, and athermal photonic design Reliability, yield, field failures, and lifetime assessment of optical components Operational experience from large-scale optical AI cluster deployments Modeling, Simulation, and Design Automation Device-to-system and electronic-photonic co-simulation methodologies Design automation, layout, and verification tools for photonic integrated circuits Digital twins and system-level simulation of optical AI clusters Modeling of collective communication performance over optical fabrics AI-Driven Design and Operation of Optical Systems Machine learning for photonic device design, inverse design, and layout optimization AI-assisted optical network planning, fault localization, and performance tuning Data-driven modeling, calibration, and control of optical transceivers and fabrics Autonomous operation, predictive maintenance, and self-optimizing optical AI clusters

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Source: Conference Partner — https://www.myhuiban.com/conference/5899 (rankings reproduced from CCF / ICORE / QUALIS; data cached up to 1 hour)