Chen-Yu Liu ^{Top-Executive}

I am a researcher specializing in quantum computing, quantum machine learning, and parameter-efficient learning techniques. I received my Ph.D. in Applied Physics from National Taiwan University in November 2025, under the supervision of Prof. Hsi-Sheng Goan. My research focuses on developing hybrid quantum–classical algorithms, such as Quantum Parameter Adaptation (QPA) and Quantum-Train (QT), that leverage quantum computation to enhance neural network training and model compression. I have published my work at leading AI and quantum computing venues, including ICLR, NeurIPS, ICASSP, IJCNN, QCE, ICTC, and QCNC, where I contributed to advancements in quantum-enhanced AI models and scalable learning strategies. Previously, I interned at Hon Hai (Foxconn) Research Institute, Jij, and Entropica Labs, where I worked on practical quantum algorithms for deep learning and optimization. My long-term goal is to bridge quantum and classical machine learning, enabling scalable and resource-efficient quantum-AI solutions.