Webber

MPhil Candidate
🌏Sydney, Australia
Unrestricted Working Rights
💼Open to Work
🎓UNSW Sydney
🧠Computer Vision
🏥Image Segmentation
🔬Evidential Deep Learning

MPhil candidate at UNSW CSE, focusing on Semi-supervised Learning, Image Segmentation, and Medical Image Processing.

📊By the Numbers

Achievements

A quick overview of milestones

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Publications
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Projects
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Awards
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GPA Rank
Featured Research

Research Highlights

Latest research achievements and technical breakthroughs

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Medical Image Segmentation

Proposed a confidence-based adaptive displacement mechanism for semi-supervised medical image segmentation. Achieved state-of-the-art performance of 90.38 DSC using only 20% labeled data on ACDC dataset.

IEEE IJCNN 2025
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Deep Learning Measurement

Utilized CNN and Transformer to fuse 3D and 2D features for accurate poultry weight and dimension prediction. Achieved MSE of 0.003 in test set, which is SOTA in this field.

Agriculture (JCR Q1)
💻Technical Skills

Tech Stack

Core technologies and development tools I work with

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AI/ML

PyTorchCNNTransformerMambaOpenCV
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Backend

Spring BootFastAPIDjangoMySQLRedisDocker
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Frontend

Vue.jsReactNext.jsTypeScriptTailwind CSS
💬Open for Collaboration

Let's Build the Future Together

Interested in AI research, full-stack development, or tech collaboration? Feel free to reach out!

Exploring the Digital Frontier | Tech Webs