Ze Wu

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Bio

I joined the Applied Bioinformatics Group in 2026 for my PhD project. My previous research focused on computer vision and digital phenotyping, including the development of lightweight and mobile deep-learning tools for wheat disease assessment, hierarchical leaf-vein segmentation, and image-based livestock phenotyping. My PhD research focuses on interpretable and robust genomic prediction in wheat, which stands at the intersection of artificial intelligence, quantitative genetics, and crop breeding.

Publications

Title Year Published by Link
Heterogeneous Deep-Ensemble Framework for Sentiment Analysis of Movie Reviews Based on Stacking and Voting 2026 Concurrency and Computation: Practice and Experience DOI
FHBDSR-Net: Automated Measurement of Diseased Spikelet Rate of Fusarium Head Blight on Wheat Spikes 2025 aBIOTECH DOI
Smartphone-based digital phenotyping for genome-wide association study of intramuscular fat traits in longissimus dorsi muscle of pigs 2024 Animal Genetics DOI
Revealing Hierarchical Structure of Leaf Venations in Plant Science via Label-Efficient Segmentation: Dataset and Method 2024 Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence DOI
StripeRust-Pocket: A Mobile-Based Deep Learning Application for Efficient Disease Severity Assessment of Wheat Stripe Rust 2024 Plant Phenomics DOI