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<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en">
<head>
<title>卢攀忠的主页</title>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta name="description" content="Lu, Panzhong is pursuing his dream">
<meta name="keywords" content="Panzhong Lu, 卢攀忠, lupanzhong, Panzhong, Lu, Deep Learning, Machine Learning, TJU, HZAU, Multimodal, Visual Language Model and Human-Computer Interaction">
<meta name="author" content="卢攀忠" />
<link rel="stylesheet" href="w3.css">
<style>
.w3-sidebar a {font-family: "Roboto", sans-serif}
body,h1,h2,h3,h4,h5,h6,.w3-wide {font-family: "Montserrat", sans-serif;}
</style>
<link rel="icon" type="image/png" href="images/pi.png">
</head>
<body class="w3-content" style="max-width:1000px">
<!-- OK - Sidebar/menu -->
<nav class="w3-sidebar w3-bar-block w3-black w3-collapse w3-top w3-right" style="z-index:3;width:150px" id="mySidebar">
<div class="w3-container w3-display-container w3-padding-16">
<h3><b>卢攀忠</b></h3>
</div>
<div class="w3-padding-64 w3-text-light-grey w3-large" style="font-weight:bold">
<a href="#home" class="w3-bar-item w3-button">主页</a>
<a href="#news" class="w3-bar-item w3-button">新闻</a>
<a href="#publications" class="w3-bar-item w3-button">出版</a>
<a href="#patents" class="w3-bar-item w3-button">专利</a>
<a href="#award" class="w3-bar-item w3-button">荣誉</a>
<!-- <a href="#projects" class="w3-bar-item w3-button">Projects</a> -->
<!-- <a href="#talks" class="w3-bar-item w3-button">Talks</a> -->
<!-- <a href="#service" class="w3-bar-item w3-button">Services</a> -->
</div>
</nav>
<!-- OK - Top menu on small screens -->
<header class="w3-bar w3-top w3-hide-large w3-black w3-xlarge">
<div class="w3-bar-item w3-padding-24">卢攀忠</div>
<a href="javascript:void(0)" class="w3-bar-item w3-button w3-padding-24 w3-right" style="font-stretch: extra-expanded;" onclick="w3_open()"><b>≡</b></a>
</div>
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<div class="w3-main" style="margin-left:150px">
<!-- Push down content on small screens -->
<div class="w3-hide-large" style="margin-top:83px"></div>
<!-- OK - The Home Section -->
<div class="w3-container w3-padding-large w3-right"><a href="https://nlpz127.github.io/homepage/">English</a>/<a href="https://nlpz127.github.io/homepage/zh.html">中文</a></div>
<div class="w3-container w3-center w3-padding-32" id="home">
<img style="width: 80%;max-width: 320px" alt="profile photo" src="images/self-portrait.png">
<h1>卢攀忠</h1>
<p class="w3-justify" style="width:100%;border:0px;border-spacing:0px;border-collapse:separate;margin-right:auto;margin-left:auto;max-width:600px">
目前我在 <a href="https://www.westlake.edu.cn/">西湖大学</a> 担任科研助理，导师是 <a href="https://scholar.google.co.uk/citations?user=6hA7WmUAAAAJ&hl=en">张岳</a> 教授。<font color="#0000FF">与此同时，我计划申请24年春季/秋季入学的博士名额</font>。我的<b>研究兴趣</b>包括但不限于<b>多/跨模态</b>, <b>人机交互</b>, <b>机器学习</b>等。 在此之前, 我在 <a href="http://www.tju.edu.cn/">天津大学</a>（2020-2023）获得了工学硕士学位，导师是 <a href="https://scholar.google.com/citations?user=k-chMpIAAAAJ&hl=en">张梅山</a> 副教授；我在 <a href="http://www.hzau.edu.cn/en/HOME.htm">华中农业大学</a>（2016-2020）获得了理学学士学位。
</p>
<p class="w3-center">
<a href="meta/CV.pdf" target="_blank">简历</a>  / 
<a href="mailto:panzhong171@gmail.com">邮箱</a>  / 
<a href="https://scholar.google.com/citations?user=5u4mhmoAAAAJ">谷歌学术</a>  / 
<a href="https://github.com/nlpz127">GitHub</a>  / 
<a href="https://twitter.com/nlpz_127">推特</a>
</p>
</div>
<!-- Update - The News Section -->
<div class="w3-container w3-light-grey w3-padding-32" id="news">
<h2>新闻</h2>
<p><li> 2023年4月，我入职 <a href="https://www.westlake.edu.cn/">西湖大学</a>，担任科研助理。</li></p>
<p><li> 2023年1月，我毕业于 <a href="http://www.tju.edu.cn/english/index.htm">天津大学</a>，获得工学硕士学位。</li></p>
<p><li> 2022年10月，我的一篇论文被 <a href="https://2022.emnlp.org/">EMNLP 2022</a> 主会接受。</li></p>
</div>
<!-- Update - The Publications Section -->
<div class="w3-container w3-padding-32"" id="publications">
<h2>出版</h2>
<!-- 可以随便讲两句 -->
<!-- <p class="w3-left-align" style="line-height:200%">
I'm interested in devleoping <strong>efficient models</strong> for computer vision (e.g. classification, detection, and super-resolution) using pruning, quantization, distilaltion, NAS, etc.
</p> -->
<!-- 会议论文 -->
<h4> 会议论文:</h4>
<ol>
<p>
<li>
<a style="color: #447ec9" href="https://aclanthology.org/2022.emnlp-main.518">
<em>Extending Phrase Grounding with Pronouns in Visual Dialogues.</em>
</a>
<br>
<strong>Panzhong Lu</strong>, Xin Zhang, Meishan Zhang, Min Zhang. <b><em>EMNLP</em></b> 2022 (CCF-B)
</li>
</p>
<p>
<li>
<a style="color: #447ec9" href="https://ieeexplore.ieee.org/document/8983031">
<em>An active gene annotation corpus and its application on anti-epilepsy drug discovery.</em>
</a>
<br>
Yuxing Wang, Kaiyin Zhou, Jin-Dong Kim, Kevin B Cohen, Mina Gachloo, Yuxin Ren, Shanghui Nie, Xuan Qin, <strong>Panzhong Lu</strong>, Jingbo Xia. <b><em>IEEE BIBM</em></b> 2019 (CCF-B)
</li>
</p>
</ol>
<!-- 期刊论文 -->
<!-- <h4> Journal Papers:</h4>
<ol>
<p>
<li><strong>GhostNets on Heterogeneous Devices via Cheap Operations</strong>
<br>
Kai Han, <strong>Panzhong Lu</strong>, Chang Xu, Jianyuan Guo, Chunjing Xu, Enhua Wu, Qi Tian
<br>
<em>IJCV</em> 2022 | <a style="color: #447ec9" href="https://link.springer.com/content/pdf/10.1007/s11263-022-01575-y.pdf">paper</a> | <a style="color: #447ec9" href="https://gitee.com/mindspore/models/tree/master/research/cv/ghostnet_d">MindSpore code</a> | <a style="color: #447ec9" href="https://github.com/huawei-noah/Efficient-AI-Backbones">Pytorch code</a>
</p>
</ol> -->
</div>
<!-- Update - The Pantents Section -->
<div class="w3-container w3-light-grey w3-padding-32" id="patents">
<h2>专利</h2>
<ol>
<!-- 张梅山, 卢攀忠, 孙越恒. 一种面向多模态的交互式数据标注方法及系统: 中国, 202210478381.9[P].2022-09-13. -->
<p>
<li>
<em>一种面向多模态的交互式数据标注方法及系统.</em>
<br>
张梅山，<strong>卢攀忠</strong>，孙越恒.
<br>
中国, 202210478381.9[P]. 2022-09-13.
</li>
</p>
<p>
<li>
<em>基于多模态语义角色识别的人机交互指令解析方法及装置.</em>
<br>
张梅山，<strong>卢攀忠</strong>，林智超，孙越恒.
<br>
中国，202210659318.5[P]. 2022-11-11.
</li>
</p>
</ol>
</div>
<!-- Update - The Awards Section -->
<div class="w3-container w3-padding-32" id="award">
<h2>荣誉</h2>
<!-- <p><li> 2017, <a href="https://research.google/outreach/phd-fellowship/recipients/?category=2017">Google PhD Fellowship</a></p> -->
<p><li> 2018，获得国家励志奖学金。</p>
<p><li> 2017，获得国家励志奖学金。</p>
</div>
<!-- OK - Bottom -->
<div class="w3-light-grey w3-center w3-padding-24">
欢迎来到卢攀忠的主页。<a href="https://nlpz127.github.io/homepage/">✩</a></br>
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https://www.wangyunhe.site -->
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</div>
<!-- 存档 -->
<!-- The Projects Section -->
<!-- <div class="w3-container w3-padding-32" id="projects">
<h2>Recent Projects</h2>
<p class="w3-justify">
Actually, model compression is a kind of technique for developing portable deep neural networks with lower memory and computation costs. I have done several projects in Huawei including some smartphones' applications in 2019 and 2020 (e.g. Mate 30 and Honor V30). Currently, I am leading the AdderNet project, which aims to develop a series of deep learning models using only additions (<a href="https://www.reddit.com/r/MachineLearning/comments/ekw2s1/r_addernet_do_we_really_need_multiplications_in/">Discussions on Reddit</a>).
</p>
<h4><li>Adder Neural Networks</li></h4>
<img style="width:96%;" src="images/AdderNet.jpg">
<p class="w3-justify">
<a style="color: #447ec9" href="https://github.com/huawei-noah/AdderNet">Project Page</a> | <a style="color: #447ec9" href="https://arxiv.org/pdf/2101.10015.pdf">Hardware Implementation</a>
</p>
<p class="w3-justify">
I would like to say, <span style="color:red">AdderNet is very cool!</span> The initial idea was came up in about 2017 when climbing with some friends at Beijing. By replacing all convolutional layers (except the first and the last layers), we now can obtain comparable performance on ResNet architectures. In addition, to make the story more complete, we recent release the hardware implementation and some quantization methods. The results are quite encouraging, we can reduce both <strong>the energy consumption and thecircuit areas significantly without affecting the performance</strong>. Now, we are working on more applications to reduce the costs of launching AI algorithms such as low-level vision, detection, and NLP tasks.
</p>
<h4><li>GhostNet on MindSpore: SOTA Lightweight CV Networks</li></h4>
<img style="width:96%;" src="images/GhostNet.png">
<p class="w3-justify">
<a style="color: #447ec9" href="https://live.huawei.com/huaweiconnect/meeting/cn/5872.html">Huawei Connect (HC) 2020</a> | <a style="color: #447ec9" href="https://www.mindspore.cn/resources/hub">MindSpore Hub</a>
</p>
<p class="w3-justify">
The initial verison of GhostNet was accepted by CVPR 2020, which achieved SOTA performance on ImageNet: <span style="color:red">75.7%</span> top1 acc with only <span style="color:red">226M FLOPS</span>. In the current version, we release a series computer vision models (e.g. int8 quantization, detection, and larger networks) on <strong>MindsSpore 1.0</strong> and <strong>Mate 30 Pro (Kirin 990)</strong>.
</p>
<h4><li>AI on Ascend: Real-Time Video Style Transfer</li></h4>
<img style="width:32%;" src="images/atlas200.png">    <img style="width:60%;" src="images/video.gif">
<p class="w3-justify">
<a style="color: #447ec9" href="https://www.huaweicloud.com/intl/en-us/HDC.Cloud.html">Huawei Developer Conference (HDC) 2020</a> | <a style="color: #447ec9" href="https://developer.huaweicloud.com/exhibition/Atlas_neural_style.html">Online Demo</a>
</p>
<p class="w3-justify">
This project aims to develop a video style transfer system on the <strong>Huawei Atlas 200 DK AI developer Kit</strong>. The latency of the original model for processing one image is about <span style="color:red">630ms</span>. After accelerating it using our method, the lantency now is about <span style="color:red">40ms</span>.
</p>
</div> -->
<!-- The Talks Section -->
<!-- <div class="w3-container w3-light-grey w3-padding-32" id="talks">
<h2>Talks</h2>
<p><li> 10/2021, Vision Transformer at <a href="http://valser.org/2021/#/tutorial">VALSE 2021, Hangzhou, China</a>.</li></p>
<p><li> 05/2021, Adder Neural Network at <a href="https://haet2021.github.io/speakers.html">HAET ICLR 2021 workshop</a>. Thanks <a href="https://datawisdom.ca/">Vahid</a> for the invitation.</li></p>
<p><li> 06/2020, "<a href="http://valser.org/webinar/slide/slides/20200603/%E6%A8%A1%E5%9E%8B%E5%8E%8B%E7%BC%A9-%E5%B7%A5%E4%B8%9A%E7%95%8C%E5%92%8C%E5%AD%A6%E6%9C%AF%E7%95%8C%E7%9A%84%E5%B7%AE%E5%BC%82.pdf">AI on the Edge - Discussion on the Gap Between Industry and Academia</a>" at <a href="http://valser.org/"><strong>VALSE</strong></a> Webinar.</li></p>
<p><li> 05/2020, "<a href="https://www.bilibili.com/video/av925692420/">Edge AI: Progress and Future Directions</a>" at <a href="https://www.qbitai.com/"> <strong>QbitAI</strong></a> using <a href="https://www.bilibili.com/"><strong>bilibili</strong></a>.</li></p>
</div> -->
<!-- The Service Section -->
<!-- <div class="w3-container w3-light-grey w3-padding-32" id="service">
<h2>Services</h2>
<p><li> Area Chair of <a href="https://icml.cc/Conferences/2023">ICML 2021</a>, <a href="https://nips.cc/Conferences/2022/">NeurIPS 2022</a>, <a href="https://icml.cc/Conferences/2021">ICML 2021</a>, <a href="https://nips.cc/Conferences/2021/">NeurIPS 2021</a>.</p>
<p><li> Action Editor of <a href="https://jmlr.org/tmlr/">TMLR</a> (Transactions on Machine Learning Research).</p>
<p><li> Senior Program Committee Members of <a href="https://ijcai-21.org/">IJCAI 2021</a>, <a href="https://www.ijcai20.org/">IJCAI 2020</a> and <a href="https://www.ijcai19.org/program-committee.html">IJCAI 2019</a>.</p>
<p><li> Journal Reviewers of <a href="https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=34">IEEE T-PAMI</a>, <a href="https://www.springer.com/journal/11263">IJCV</a>, <a href="https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=83">IEEE T-IP</a>, <a href="https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5962385">IEEE T-NNLS</a>, <a href="https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6046">IEEE T-MM</a>, <a href="https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=69">IEEE T-KDE</a>, etc.</p>
<p><li> Program Committee Members of ICCV 2021, AAAI 2021, ICLR 2021, NeurIPS 2020, ICML 2020, ECCV 2020, CVPR 2020, ICLR 2020, AAAI 2020, ICCV 2019, CVPR 2019, ICLR 2019, AAAI 2019, IJCAI 2018, AAAI 2018, NeurIPS 2018, etc.</p>
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