جستجوی استاد راهنمای دانشگاهی

Terence Broad is a researcher at Goldsmiths, University of London , specializing in generative neural networks and computational creativity. His work bridges machine learning with artistic expression, focusing on techniques like network bending and active divergence to push generative models beyond data imitation. Broad's research includes data-free methods, divergent fine-tuning, and expressive manipulation of deep generative models. Thesis : Expanding the Generative Space (2025) presents novel approaches for active divergence in generative systems. Key Contributions : Pioneered network bending frameworks for feature manipulation, explored uncanny amplification in deepfakes, and developed autoencoder-based film reconstruction systems. His publications span conferences like ICCC’21, EvoMUSART 2021, and SIGGRAPH 2016, demonstrating applications in image, audio, and video domains. Broad's collaborations with Frederic Fol Leymarie and Mick Grierson highlight interdisciplinary approaches to machine-generated creativity.

• Generative Neural Networks
• Computational Creativity
• Deep Learning
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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.

• Natural Language Processing
• Text Mining
• Machine Learning
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