Congratulations to E. Xie (F.4) for publishing his paper titled “Quantum Surrogate-Driven Image Classifier: A Gradient-Free Approach to Avoid Barren Plateaus” at the IEEE qCCL2025 conference held at PolyU from June 25th to 28th. As the only high school student at the event,  E. Xie earned high praise from reviewers, professors, and attendees.

His research focuses on optimizing quantum circuits using a surrogate neural network. It theoretically mitigates barren plateaus by avoiding the backpropagation of loss function gradients during training. This innovative approach highlights the potential of quantum computing in image classification.

E. Xie’s work stands out not only for its technical depth but also for its relevance in the rapidly evolving field of quantum machine learning. His achievement is a testament to his hard work and dedication, as well as the support he received from the conference chair.

Congratulations to E. Xie on this remarkable accomplishment! We look forward to his future contributions to the field.