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<!DOCTYPE html>
<html lang="zh-cn">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1">
<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, minimum-scale=1.0, user-scalable=no"
/>
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<title>Zhexiao Xiong's CV</title>
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<link rel="stylesheet" href="assets/css/index.css">
</head>
<body>
<header class="header"></header>
<article class="container">
<section class="side" id="side">
<!-- 左栏固定开关，记得及时删除这段代码 Start-->
<!-- <label class="switch" style="display: none;" onchange="switchFixed()">
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<style>
@media (min-width: 750px){
.switch{position:relative;display:inline-block!important;width:60px;height:34px;}
.switch input{display:none;}
.slider{position:absolute;cursor:pointer;top:0;left:0;right:0;bottom:0;background-color:#ccc;-webkit-transition:.4s;transition:.4s;}
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.slider.round:before{border-radius:50%;}
}
</style>
<!-- 左侧固定开关，记得及时删除这段代码 End-->
<!-- 个人肖像 -->
<section class="me">
<section class="portrait">
<div class="loading">
<span></span>
<span></span>
<span></span>
<span></span>
<span></span>
</div>
<!-- 头像照片 -->
<img id=avatar class="avatar" src="./assets/images/cartoon.jpg">
<script type="text/javascript">
avatar.onload = function() {
setTimeout(function(){
document.getElementsByClassName('avatar')[0] .style.display = 'block';
document.getElementsByClassName('loading')[0] .style.display = 'none';},1000)
}
</script>
</section>
<h1 class="name">Zhexiao Xiong</h1>
<h4 class="info-job">Senior of Tianjin University</h4>
</section>
<!-- 基本信息 -->
<section class="profile info-unit">
<h2>
<i class="fa fa-user" aria-hidden="true"></i>Personal Information</h2>
<hr/>
<ul>
<li>
<label>Name:</label>
<span>Zhexiao Xiong </span>
</li>
<li>
<label>TOEFL:</label>
<span>100 <br> MyBest:111 (Listening: 29 Reading: 30 Writing: 28 Speaking: 24)</span>
</li>
<li>
<label>GRE:</label>
<span>335 (166(V)+169(Q))</span>
</li>
<li>
<label>GPA:</label>
<span>86.2/100(3.64/4.0(WES))</span>
</li>
</ul>
</section>
<section class="contact info-unit">
<h2>
<i class="fa fa-phone" aria-hidden="true"></i>Contact Information</h2>
<hr/>
<ul>
<li>
<label>tel:</label>
<a href="tel:+86 13721783286" target="_blank">+86 13721783286</a>
</li>
<li>
<label>e-mail:</label>
<a href="[email protected]" target="_blank">[email protected]</a>
</li>
<!-- <li>
<label>个人主页</label>
<a href="http://www.duang.com/" target="_blank">oduang.com/</a>
</li>
<li>
<label>Github</label>
<a href="https://github.com/oduang" target="_blank">github.com/oduang</a>
</li> -->
</ul>
</section>
<section class="skill info-unit">
<h2>
<i class="fa fa-code" aria-hidden="true"></i>Programming</h2>
<hr/>
<ul>
<li>
<label>python</label>
<progress value="90" max="100"></progress>
</li>
<li>
<label>C++</label>
<progress value="85" max="100"></progress>
</li>
<li>
<label>Matlab</label>
<progress value="70" max="100"></progress>
</li>
<li>
<label>Java</label>
<progress value="70" max="100"></progress>
</li>
</ul>
</section>
<section class="skill info-unit">
<h2>
<i class="fa fa-code" aria-hidden="true"></i>Deep Learning Framework</h2>
<hr/>
<ul>
<li>
<label>pytorch</label>
<progress value="90" max="100"></progress>
</li>
<li>
<label>Tensorflow</label>
<progress value="80" max="100"></progress>
</li>
</ul>
</section>
<!-- <section class="qrcode info-unit">
<h2><i class="fa fa-qrcode" aria-hidden="true"></i>二维码</h2>
<hr/>
<img src="https://github.com/if2er/FeZaoDuKe-Collection/blob/master/ifeees.jpg?raw=true" style="width: 100%;" alt="">
</section> -->
<!-- 技术栈 -->
<!-- <div class="stack info-unit">
<h2><i class="fa fa-code" aria-hidden="true"></i>其他</h2>
<hr/>
<ul>
<li>
<label>前端</label>
<span>React、jQuery、微信小程序、Bootstrap、SASS、LESS</span>
</li>
<li>
<label>后端</label>
<span>Node.js、MySQL、MongoDB、WordPress、ThinkPHP</span>
</li>
<li>
<label>其他</label>
<span>Git、SVN、Markdown</span>
</li>
</ul>
</div> -->
</section>
<section class="main">
<!-- 教育经历 -->
<section class="edu info-unit">
<h2>
<i class="fa fa-graduation-cap" aria-hidden="true"></i>EDUCATION</h2>
<hr/>
<ul>
<li>
<h3>
<span>Tianjin University - B.S. in Communication Engineering </span>
<time>09/2018 - 07/2022 (Expected)</time>
</h3>
<p>scholarship:
<mark> People’s Scholarship of Tianjin University </mark>
</li>
</ul>
</section>
<!-- publication -->
<section class="edu info-unit">
<h2>
<i class="fa fa-graduation-cap" aria-hidden="true"></i>PUBLICATION</h2>
<hr/>
<ul>
<li>
<h3>
<span> Zhexiao Xiong, Xin Wen, Xu Zhao*, Haiyun Guo, Chaoyang Zhao, Jinqiao Wang.
Two-level Iteration Method for Multi-task Learning with Task-isolated Labels, International Conference on Computer Vision and Pattern Analysis, 2021.</span>
<time> </time>
</h3>
</li>
<li>
<h3>
<span> Nanfei Jiang, Xu Zhao, Chaoyang Zhao, Pengkun Liu, Zhexiao Xiong, Yongqi An, Ming Tang, Jinqiao Wang.
Pruning-aware Sparse Regularization for Network Pruning, AAAI Conference on Artificial Intelligence, 2022. (Under review). </span>
<time> </time>
</h3>
</li>
<li>
<h3>
<span> Nanfei Jiang, Zhexiao Xiong, Hui Tian, Xu Zhao, Xiaojie Du, Chaoyang Zhao*, Jinqiao Wang.
PruneFaceDet: Pruning Lightweight Face Detection Network by Sparsity Training, Cognitive Computation and Systems, 2021. </span>
<time> </time>
</h3>
<!-- <p>GPA:
<mark>X/XX</mark>，期间发表国际会议英文摘要X篇，国内核心期刊文章X篇（其中第一作者X篇），获XXX，XXX2次，XXX2次。(此处根据自身情况填写，可以突出自己的亮点，或者跟求职目标相关的内容)</p> -->
</li>
</ul>
</section>
<!-- RESEARCH EXPERIENCE -->
<section class="work info-unit">
<h2>
<i class="fa fa-shopping-bag" aria-hidden="true"></i>RESEARCH EXPERENCE</h2>
<hr/>
<ul>
<li>
<h3>
<span>
Research Intern, Intelligent Perception and Interaction Research Department, OPPO Research, Beijing <br>
</span>
<time>02/2022 - Present</time>
</h3>
<ul class="info-content">
<li>Research in image matting combined with human pose estimation.
</ul>
</li>
<li>
<h3>
<span>Visual Transformer pruning on multitask face attribute recognition <br>
Graduation Thesis <br>
Supervisor: Prof.Xu Zhao & Prof.Weizhi Nie
</span>
<time>01/2022 - present</time>
</h3>
<ul class="info-content">
<li>Build multitask transformer on face attribute recognition task.
<li>Propose a structured pruning approach based on L0 and L2 sparsity regularization, achieving well-balanced in
accuaracy and speed.
<li>Apply my Visual Transformer pruning method on multitask face attribute learning.
</ul>
</li>
<li>
<h3>
<span>Two-level Iteration Method for Multi-task Learning with Task-isolated Labels <br>
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences <br>
Supervisor: Prof. Jinqiao Wang
</span>
<time>05/2021 - 10/2021</time>
</h3>
<ul class="info-content">
<li>Proposed a two-level iteration method based on multi-task learning,
including the task-level inner iteration and regular outer iteration, which achieves training with task-isolated labels.
<li>Achieved training multi-task face attribute recognition networks without the need for full annotations of all images.
<li>Achieved higher accuracy and lower computation costs than single-task learning on CelebA, MORPH II, and self-collected datasets.
</ul>
</li>
<li>
<h3>
<span>Face Anti-Spoofing <br>
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences <br>
Supervisor: Prof. Jinqiao Wang
</span>
<time>04/2021 - 12/2021</time>
</h3>
<ul class="info-content">
<li>Built face anti-spoofing model based on CelebA-Spoof, CASIA-SURF-CeFA and LCC-FASD dataset.
<li>Used detection methods based on RetinaFace and designed network architecture based on MobileNet and CDCN++, including multi-task learning.
<li>Used model compression and knowledge distillation to reduce the float-point-operations and run-time memory of the model.
<li>Plan to submit a paper based on the work this fall.
</ul>
</li>
<li>
<h3>
<span>Pruning-aware Sparse Regularization for Network Pruning <br>
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences <br>
Supervisor: Prof. Jinqiao Wang
</span>
<time>01/2021 - 09/2021</time>
</h3>
<ul class="info-content">
<li>Proposed a novel pruning method, MaskSparsity, with pruning-aware sparse regularization.
<li>Only applied the sparse regularization on the unimportant channels
to be pruned and minimized the negative impact of the sparse regularization on important channels.
<li>Achieved 63.03%-FLOPs reduction on ResNet-110 by removing 60.34% of the parameters with no
top-1 accuracy loss on CIFAR-10, which exceeds the previous state-of-the-art performance.
<li>Reduced more than 51.07% FLOPs on ResNet-50 with only a loss of 0.76% in the top-1 accuracy,
which shows superiority over the previous state-of-the-art methods.
</ul>
</li>
<li>
<h3>
<span>Pruning Lightweight Face Detection Network by Sparsity Training <br>
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences <br>
Supervisor: Prof. Jinqiao Wang </span>
<time>01/2021 - 07/2021</time>
</h3>
<ul class="info-content">
<li>Used network slimming algorithms, including structured sparsity and optimal thresholding to reduce the parameters, float-point-operations, and run-time memory of the model.
<li>Performed the network training with sparsity regularization on channel scaling factors of each layer,
and then removed the connections and the corresponding weights with the near-zero scaling factors after the sparsity training.
<li>Applied the proposed pruning pipeline on a state-of-the-art face detection method,
EagleEye, and got a shrunken model which has a reduced number of computing operations and parameters.</li>
<li>Achieved 56.3% reduction of parameter size with almost no accuracy loss on WiderFace dataset.
</ul>
</li>
<li>
<h3>
<span>Cross-domain Object Detection Using Domain Adaptation <br>
Multimedia Processing Lab, TJU <br>
Supervisor: Associate Prof. Yuenan Li
</span>
<time>07/2020 – 03/2021</time>
</h3>
<ul class="info-content">
<li>Used Pytorch to implement object detection and image dehazing tasks in different background situations.
<li>Combined detection methods such as Cascade R-CNN with ART, RPN, PSA, and GAN modules to build the object detection network.
</ul>
</li>
<li>
<h3>
<span>Colorization of Images and Cartoon Pictures Based on Generative Adversarial Network <br>
Innovation and Entrepreneurship Training Program, TJU <br>
Team Leader Supervisor: Prof. Zhong Ji
</span>
<time>05/2020 - 05/2021</time>
</h3>
<ul class="info-content">
<li>Built Generative Adversarial Network (GAN) based on Pytorch and changed the structure of
GAN to improve the accuracy based on the ChromaGAN by adjusting the parameters and changing the architecture of generator and loss function.
<!-- <mark>React+React Router+Node.js+SASS</mark>，实现
<mark>前后端完全分离</mark>。</li> -->
<li>Proposed the research plan, sought for background algorithms, and implemented them.
<!-- <mark>移动端显示正常</mark>。</li> -->
<li>Wrote a project final report and successfully passed the reply.
<!-- <mark>在支付宝环境下完全兼容</mark>。</li> -->
</ul>
</li>
</ul>
</section>
<!-- 项目经验 -->
<section class="project info-unit">
<h2>
<i class="fa fa-terminal" aria-hidden="true"></i>PROJECT EXPERIENCE
</h2>
<hr/>
<ul>
<li>
<h3>
<span>Mobile AI 2021 Real-Time Camera Scene Detection Challenge </span>
<!-- <span class="link">
<a href="#" target="_blank">Demo</a>
</span> -->
<time>03/2021</time>
</h3>
<ul class="info-content">
<li>CodaLab Competition: Mobile AI Workshop @ CVPR 2021</li>
<li>
<i class="fa fa-paper-plane-o" aria-hidden="true"></i>
Achieved Fast Camera Scene Detection via Light-weight Network Designing and Model Pruning.
<br/>
<i class="fa fa-users" aria-hidden="true"></i>
Used the two-stage fine-tuning method to improve the accuracy and the model pruning method to improve the model’s efficiency.
<br/>
<i class="fa fa-bars" aria-hidden="true"></i>
Converted the pretrained Pytorch model to Tensorflow and used the float32-to-int8 quantization and model pruning methods to optimize our model.
<br/>
<i class="fa fa-thumbs-o-up" aria-hidden="true"></i>
<mark>Submitted the final TFLite model which can be deployed on mobile platforms and got a top 10 score in the evaluation.</mark> </li>
</ul>
</li>
<li>
<h3>
<span>Brain Tumor Detection and COVID19 Diagnosis Based on Convolutional Neural Network</span>
<!-- <span class="link">
<a href="#" target="_blank">Demo</a>
</span> -->
<time>07/2020 - 08/2020</time>
</h3>
<ul class="info-content">
<li>Data Science Summer School, Imperial College London </li>
<li>
<i class="fa fa-paper-plane-o" aria-hidden="true"></i>
Used TensorFlow to deal with medical images classification and segmentation problems and finished the project CNN based Brain Tumor Detection and COVID19 diagnosis.
<br/>
<!-- <i class="fa fa-users" aria-hidden="true"></i>
[团队]与 1 位同学 -->
<!-- <br/> -->
<i class="fa fa-bars" aria-hidden="true"></i>
Mastered and implemented robot visual orientation and SLAM based on MATLAB.
<!-- <mark>D3.js</mark> 和
<mark>ECharts</mark> 进行图形化展示以及实现简易自动分析 功能 -->
<br/>
<i class="fa fa-thumbs-o-up" aria-hidden="true"></i>
<mark>Got A Distinction in the program.</mark>
</li>
</ul>
</li>
<li>
<h3>
<span>Analysis of Customers’ Reviews and Star Ratings </span>
<!-- <span class="link">
<a href="#" target="_blank">Demo</a>
</span> -->
<time>03/2020</time>
</h3>
<ul class="info-content">
<li>The Mathematical Contest in Modeling（MCM）</li>
<li>
<i class="fa fa-paper-plane-o" aria-hidden="true"></i>
Used machine learning methods and natural language processing methods based on the given star ratings and feedback data of the customers.
<br/>
<!-- <i class="fa fa-users" aria-hidden="true"></i>
[团队]与 1 位同学 -->
<!-- <br/> -->
<i class="fa fa-bars" aria-hidden="true"></i>
Used machine learning methods and natural language processing methods based on the given star ratings and feedback data of the customers.
<!-- <mark>D3.js</mark> 和
<mark>ECharts</mark> 进行图形化展示以及实现简易自动分析功能 -->
<br/>
</li>
</ul>
</li>
</ul>
</section>
<!-- SKILLS -->
<section class="work info-unit">
<h2>
<i class="fa fa-pencil" aria-hidden="true"></i>SKILLS</h2>
<hr/>
<p> Programming: Python, C++, MATLAB, Java <br>
Deep Learning: PyTorch, TensorFlow <br>
Embedded System Developing: C51, Arduino, FPGA <br>
Instrument: Flute, Guitar <br>
<span class="mark-txt">"Stay hungry. Stay foolish"</span>is my motto. It spurs me to keep on exploring the unknown realm with modesty. </p>
</section>
</section>
</article>
<footer class="footer">
<p>© 2022 Zhexiao Xiong. The lataset update:
<time>2022.4.28</time>.</p>
</footer>
<!-- 侧栏 -->
<!-- <aside>
<ul>
<li>
<a href="https://github.com/oduang/resume" target="_blank">源代码</a>
</li>
<li>
<a href="https://www.oduang.com/" target="_blank">Blog</a>
</li>
</ul>
</aside> -->
<script src="./assets/js/index.js"></script>
</body>
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