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Applied Quantum Machine Learning: From Quantum Circuits to Smart Systems
Workshop at IJCNN | IEEE WCCI 2026
Location: MECC Maastricht, Room: 2.2 Zambezi
This workshop aims to advance the translation of quantum circuits into deployable, domain-driven intelligent systems by gathering methods, systems, and applications in Quantum Machine Learning (QML). We emphasize hybrid pipelines, reliability under noise and errors, interpretability, security and privacy, and benchmarking that links algorithms to real hardware and latency constraints. Submissions spanning theory, software/hardware co-design, and case studies in finance, healthcare, transportation, climate, cybersecurity, networks, and IoT are especially encouraged.
List of Topics (preferred, but not restricted to)
List of Topics (preferred, but not restricted to)
Cross-cutting QML Methods
– Hybrid quantum-classical learning pipelines
– Quantum representation learning & embeddings
– Interpretable & trustworthy QML
– Robust QML under noise
– Benchmarking & reproducibility for QML
– Hardware-aware QML
– Security and Privacy in QML
Applied QML
– Quantum Finance
– Quantum Healthcare
– Transportation & Mobility
– Climate & Weather
– Cybersecurity
– Materials & Chemistry
– Telecom & Networks
– Smart Cities & IoT
Optimization & Reliability
– QML architecture/search
– Training quantum Reinforcement Learning agents
– Variational optimization at scale
– Error mitigation and correction for QML
Generative & Foundation Models
– Quantum GANs & VAEs for simulation/synthetic data
– Generative agents for QML pipeline design
– Multimodal & retrieval-augmented QML
Speakers
Speakers
Muhammad Usman
(CSIRO, University of Melbourne, AU)
Samuel Yen-Chi Chen
(Wells Fargo, US)
Giovanni Acampora
(University of Naples Federico II, IT)
Pierre-Emmanuel Emeriau
(Quandela, FR)
Amir Pourabdollah
(Nottingham Trent University, UK)
Akash Kundu
(Delft University of Technology and QuTech, NL)
Antonello Rosato
(Sapienza University of Rome, IT)
Organizers
Organizers
Nouhaila Innan
(New York University Abu Dhbai, UAE)
Alberto Marchisio
(New York University Abu Dhbai, UAE)
Muhammad Kashif
(New York University Abu Dhbai, UAE)
Muhammad Shafique
(New York University Abu Dhbai, UAE)
Schedule
Schedule
Schedule
Schedule
9:00 - 11:00 Session 1: Opening and Invited Talks
– 9:00 - 9:15 Opening Remarks
– 9:15 - 9:45 Samuel Yen-Chi Chen - Learning to Design Quantum Intelligent Systems: From Quantum Circuits to Recurrent QML, Quantum Agents, and Architecture Search
– 9:55 - 10:25 Giovanni Acampora - Synergies between Quantum Computing and Machine Learning: Evolutionary Optimization and Reinforcement Learning for Quantum Circuit Design
– 10:30 - 11:00 Pierre-Emmanuel Emeriau - From Photonic Circuits to Trainable Quantum Machine Learning Models
11:00 - 11:30 Coffee Break
11:30 - 12:30 Session 2: Panel Discussion
12:30 - 13:30 Lunch Break
13:30 - 15:30 Session 3: Invited Talks
– 13:30 - 14:00 Muhammad Usman - Machine Learning with Qubits for Robust Autonomous Systems
– 14:10 - 14:40 Antonello Rosato - Why Hyperdimensional Computing Matters for Quantum Machine Learning Applications
15:30 - 16:00 Coffee Break
16:00 - 17:25 Session 4: Invited Talks and Closing
– 16:00 - 16:30 Akash Kundu - Towards a Scalable and QPU-Aware Quantum Architecture Search with Reinforcement Learning
– 16:40 - 17:10 Amir Pourabdollah - From Quantum Annealing to QAOA, and to FPGA-based Simulation
– 17:15 - 17:25 Closing
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