معرفی
Hsin-Yi Lin is an Assistant Professor in the Department of Mathematics and Computer Science at Seton Hall University. Her research focuses on quantum machine learning, speech enhancement, and data assimilation with applications in computational physics and neural network interpretability. She explores interdisciplinary topics including quantum neural networks, adversarial robustness in speech models, and multi-scale geophysical dynamics modeling.
Recent work emphasizes quantum measurement optimization, transfer learning in quantum circuits, and novel diffusion models. Her publications address challenges in speech quality assessment, domain adaptation, and scalable state estimation using recurrent networks. She has contributed to foundational mathematical analysis of transport equations and developed extensions to signal processing frameworks like SEMamba.
Key research themes include hybrid quantum-classical systems, explainable AI for quantum models, and robust machine learning under adversarial conditions. Collaborations bridge theoretical mathematics with applied computational methods in earth system prediction and periodic migration modeling.
