This is a match-making section for QuantERA Call 2025.
Quantum Machine Learning Optimization Hybrid Quantum-AI Artificial Intelligence
We are looking for research and industry partners interested in exploring hybrid quantum-AI applications in real-world domains such as e-commerce, logistics, and production systems. Ideal partners bring complementary expertise in quantum algorithms, hardware implementation, supply chain modeling, or industrial data ecosystems. We aim to collaborate within a multidisciplinary consortium that connects academic research, technology providers, and industrial end-users to jointly develop and validate quantum-enhanced optimization and learning solutions. Our goal is to demonstrate measurable impact through quantum-enabled efficiency gains in complex decision processes such as returns management, demand forecasting, and resource allocation.
The project aims to design Hybrid Quantum-AI frameworks that combine classical artificial intelligence with quantum computing to improve demand forecasting, routing, and dynamic inventory allocation. By leveraging Quantum Machine Learning and quantum optimization algorithms, the project will enable more efficient decision-making under uncertainty reducing return rates, minimizing transport emissions, and improving resource utilization. Potential use cases include: Quantum-based optimization for routing and warehouse allocation in reverse logistics, Hybrid AI models for predicting return probabilities and product lifecycle outcomes, Quantum-classical decision support systems for sustainable supply chain management. The August-Wilhelm Scheer Institute contributes expertise in applied AI, hybrid quantum-AI architectures, and process innovation, focusing on translating quantum advances into scalable digital solutions for industry.
Submitted on 2025-10-30 11:58:20
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