量子軟體技術研究團隊

本研究以語音與自然語言處理、情感計算及多模態學習為核心，結合國家量子AI計算中心之高效能運算資源，發展新世代生成式AI、多模態大型模型及可信賴人工智慧技術。透過跨模態表示學習、語意理解、模型最佳化與高效能運算架構，提升人工智慧模型的效能、泛化能力與推論效率，推動AI基礎技術發展及跨領域創新應用。

My research focuses on Speech and Language Processing, Affective Computing, and Multimodal Learning, leveraging the high-performance computing infrastructure of the National Quantum AI Computing Center. My work aims to advance next-generation generative AI, multimodal foundation models, and trustworthy AI technologies. By integrating multimodal representation learning, semantic understanding, model optimization, and scalable computing architectures, I seek to improve the performance, generalization, and inference efficiency of AI models. This research contributes to the development of core AI technologies while enabling innovative cross-disciplinary applications and fostering the next generation of intelligent computing systems.