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<h3>PhD in Computer Science</h3>
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<span>The University of Adelaide</span>
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<h1>Biography</h1>
<p>Hao Chen is currently a CV researcher @ Noah’s Ark Lab in Huawei. He got his PhD degree of computer science in
<a href="https://github.com/aim-uofa" target="_blank" rel="noopener">Adelaide Intelligent Machines Group</a> at
<a href="https://www.adelaide.edu.au/" target="_blank" rel="noopener">the University of Adelaide</a>. He was advised by Professor
<a href="https://cs.adelaide.edu.au/~chhshen/" target="_blank" rel="noopener">Chunhua Shen</a>. Before Adelaide he obtained his undergraduate and master degree from Zhejiang University, and had been a researcher in NetEase Inc.</p>
<p>He anticipates to graduate in late 2020.</p>
<p>His general research interest lies in probabilistic methods for general perception tasks in computer vision. His recent research involves:</p>
<ul>
<li>Fast NAS: computation-friendly neural architecture search (NAS) with reinforcement learning for segmentation, detection and low-level tasks.</li>
<li>BlendMask: a general instance segmentation framework which is both faster and more efficient than Mask-RCNN.</li>
<li>AdelaiDet: a collection of recent projects dealing with different instance-level tasks.</li>
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<li>Machine Learning</li>
<li>Computer Vision</li>
<li>Bayesian Deep Learning</li>
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<p class="institution">The University of Adelaide</p>
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<p class="course">MSc in Computer Science, 2016</p>
<p class="institution">Zhejiang University</p>
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<p class="course">BSc in Computer Science, 2013</p>
<p class="institution">Zhejiang University</p>
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<h3 class="article-title mb-0 mt-0">
<a href="/post/2020-03-01-cvpr-2020/" >Four Papers Got Accepted at CVPR 2020</a>
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All papers are available on arxiv.
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Last updated on
Mar 13, 2020
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1 min read
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<a href="/post/2020-03-01-cvpr-2020/#disqus_thread"></a>
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<h3 class="article-title mb-0 mt-0">
<a href="/post/2020-01-04-faster-and-finer-instance-segmentation-with-blendmask/" >Faster and Finer Instance Segmentation With Blendmask</a>
</h3>
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Introduction to our new instance segmentation model, BlendMask, which generates higher qualities than Mask R-CNN while being faster in inference.
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