معرفی
Yuping Wu is a researcher specializing in Natural Language Processing, Text Mining, and Machine Learning. Her work focuses on enhancing large language models, data augmentation, and attention mechanisms in computational linguistics and clinical domains. She actively contributes to peer-reviewed research outputs in conferences like EACL, ProbSum, and journals such as Entropy.
- Research areas: Natural Language Processing, Machine Learning, Data Augmentation, Clinical Informatics, Large Language Models, and Text Mining.
- Key publications: Extractive summarization, clinical named entity recognition, data augmentation with black-box LLMs, attention networks in computer vision, and cost index prediction models.
- Collaborations: Active with teams like PULSAR and researchers including X. Zeng, G. Nenadic, and V. Schlegel.
Her research spans artificial intelligence, computer vision, and healthcare text mining, often leveraging transformer architectures and neural network innovations. She explores applications in clinical data summarization and construction cost forecasting, demonstrating interdisciplinary impact through UN Sustainable Development Goals (SDGs) related to technological advancement and healthcare.
