Yue Wu, Associate Professor, Ph.D. Supervisor at the School of Computer Science and Technology, Xidian University, Shaanxi Youth Science and Technology New Star, IEEE/CCF/CAAI Senior Member, Secretary-General of the CAAI Youth Committee, Executive Member of CCF Xi’an, Chair of CCF YOCSEF Xi’an, Secretary-General of CCF Xi’an Branch. His research interests include computational intelligence and 3D computer vision.

He received the B.Eng. and Ph.D. degrees from Xidian University, Xi’an, China, in 2011 and 2016, respectively. Since 2016, he has been a Teacher with Xidian University. He has published over 50 papers as the first/corresponding author in SCI A1 or CCF-A journals/conference, and 10 papers have been selected as ESI highly cited papers, which have been cited over 3,800 times. He is selected for Stanford University Top 2% Scientists List (2022-2024). He has applied and authorized over 50 patents. He is leading or has completed more than 20 projects as the principal investigator, including National Natural Science Foundation of China (Key Program, General Program, Youth Program), Natural Science Basic Research Program of Shaanxi (General Program, Youth Program), China Postdoctoral Foundation (Special Foundation, General Program), SAST Fund, and the CAAI-Huawei MindSpore Academic Fund. He has won over 10 academic awards as the first principal investigator, including Second Prize for Science and Technology Award of Shaanxi Province, Outstanding Youth Award of Wu Wenjun AI Science & Technology, Youth Science and Technology Star of Shaanxi Province, and Huawei Spark Award. He serves as the Secretary-General of the Youth Committee of the CAAI, the Chair of CCF YOCSEF Xi’an, and the Secretary-General of the CCF Xi’an Branch. He is also the Associate Editor for Expert Systems with Applications, IEEE Transactions on Emerging Topics in Computational Intelligence, and the Editorial Board Member for Frontiers of Computer Science and CAAI Transactions on Intelligence Technology.

Education Experience:

• 2007.09-2011.06      Bachelor, School of Electronic Engineering, Xidian University
• 2011.08-2016.06      Ph.D (advised by Professor Maoguo Gong), School of Electronic Engineering, Xidian University

Working Experience:

• 2016.09-2019.06      Lecturer, School of Computer Science and Technology, Xidian University
• 2019.06-Present      Associate Professor, School of Computer Science and Technology, Xidian University

Academic Service

Academic Organizations Serving:

• The Secretary-General of the Youth Committee of the CAAI (2022-present)
• The Chairperson of CCF YOCSEF Xi'an (2021-2022)
• The Secretary-General of the CCF Xi'an Branch (2020-2022)
• IEEE Senior Member (2024-present)
• The Member of the Committee on 3D Vision of the China Society for Image and Graphics (2022-present)

Academic Journals Serving:

• Associate Editor of Expert Systems with Applications (IF: 7.5, SCI A1 TOP) (2024-present)
• Associate Editor of Swarm and Evolutionary Computation (IF: 10.0, SCI A1) (2024-present)
• Associate Editor of IEEE Transactions on Emerging Topics in Computational Intelligence (IF: 5.3) (2024-present)
• The editorial board member for Frontiers of Computer Science (CCF B) (2022-present)
• The editorial board member for CAAI Transactions on Intelligence Technology (SCI A2) (2022-present)
• Special Issue Editor of Remote Sensing (SCI A2) (2022-present)

Academic Conferences Serving:

• PC Member for the 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
• PC Member for the 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024)
• PC Member for the 37th AAAl Conference on Artificial Intelligence (AAAI 2023)
• PC Member for the 31st ACM International Conference on Multimedia (ACM MM 2023)
• TC Member for the 8th IEEE International Conference on Cloud Computing and Intelligent Systems (IEEE CCIS 2022)
• OC Chair for the 7th IEEE International Conference on Cloud Computing and Intelligent Systems (IEEE CCIS 2021)
• Registration Chair for the 11th International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA 2016)
• Vice Chair of Publications for the 6th CCF Big Data (2018)

Research Interests

• Computational Intelligence Theory and Applications (Evolutionary computation, Machine Learning, Neural Networks etc.)
• 3D Computer Vision (Point Cloud Understanding, Registration, Detection, Tracking, Reconstruction etc.)
• Image Processing and Pattern Recognition

Awards

• Science and Technology Award of Shaanxi Province, Second Prize, 2023（2023年陕西省科学技术奖自然科学二等奖, 1/6）
• Award of Wu Wenjun AI Science & Technology, Outstanding Youth, 2023（2023年吴文俊人工智能优秀青年奖, 1/1）
• Youth Science and Technology Star of Shaanxi Province, 2023（2023年陕西省青年科技新星, 1/1）
• ACM China (Xi’an), Rising Star Award, 2020. （2020年ACM中国新星奖（西安）, 1/1）
• AAAI2024 Outstanding Paper Award, 2024（2024年第38届AAAI人工智能大会（AAAI2024）杰出论文奖, 5/6）
• Huawei Spark Award, 2022（2022年华为火花奖, 1/1）
• Shaanxi Provincial Institute of Electronics Science and Technology Award for Natural Science, Second Prize, 2022（2022年陕西省电子学会科学技术奖自然科学二等奖, 1/4）
• The 7th National Youth Artificial Intelligence Innovation and Entrepreneurship Conference, First prize, 2022（2022年第7届全国青年人工智能创新创业大会创新组一等奖, 1/6）
• Shaanxi Innovation and Entrepreneurship Competition For Scientific and Technical Professionals, Gold Award, 2018（2018年陕西省科技工作者创新创业大赛金奖, 2/6）
• The 6th IEEE ACAIT, Best paper, 2022（2022年第6届IEEE亚洲人工智能技术大会最佳论文, 1/6）
• The 15th CIS, Best student paper, 2019（2019年国际计算智能与安全会议最佳学生论文, 4/5）
• The 5th CHREOC, Best paper, 2018（2018年第5届高分辨率对地观测学术年会优秀论文奖, 2/5）
• Huawei MindSpore Open Source Community Excellence, Mentorship Award, 2023（2023年华为昇思MindSpore开源社区卓越指导教师奖, 1/1）
• Outstanding Association Worker of the CAAI, 2020（2020年中国人工智能学会优秀学会工作者, 1/1）

Publications

Journals:

• Maoguo Gong, Yuan Gao, Yue Wu, Yuanqiao Zhang, A. K. Qin, Yew Soon Ong, “Heterogeneous Multi-Party Learning With Data-Driven Network Sampling", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(11), pp. 13328 - 13343, 2023.(CCF A, IF=23.6) [Paper] [Code]
• Yue Wu, Yue Zhang, Wenping Ma, Maoguo Gong, Xiaolong Fan, Mingyang Zhang, A. K. Qin, Qiguang Miao, “RORNet: Partial-to-Partial Registration Network With Reliable Overlapping Representations", IEEE Transactions on Neural Networks and Learning Systems (TNNLS), pp. 1 - 14, 2023.(IF=10.4) [Paper] [Code]
• Yue Wu, Jiaheng Li, Yongzhe Yuan, A. K. Qin, Qiguang Miao, Maoguo Gong “Commonality Autoencoder: Learning Common Features for Change Detection from Heterogeneous Images", IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 33(9), pp. 4257 - 4270, 2022. (IF=10.4) [Paper] [Code]
• Wenping Ma, Mingyu Yue, Yue Wu(Corresponding Author), Yongzhe Yuan, Hao Zhu, Biao Hou, Licheng Jiao, “Explore the Influence of Shallow Information on Point Cloud Registration", IEEE Transactions on Neural Networks and Learning Systems (TNNLS), pp. 1 - 13, 2023.(IF=10.4) [Paper] [Code]
• Yue Wu, Jinlong Sheng, Hangqi Ding, Peiran Gong, Hao Li, Maoguo Gong, Wenping Ma, Qiguang Miao, “Evolutionary Multitasking Descriptor Optimization for Point Cloud Registration", IEEE Transactions on Evolutionary Computation (TEVC), pp. 1 - 1, 2024.(IF=11.7) [Paper]
• Yue Wu, Hangqi Ding, Maoguo Gong, A. K. Qin, Wenping Ma, Qiguang Miao, Kay Chen Tan, “Evolutionary Multiform Optimization With Two-Stage Bidirectional Knowledge Transfer Strategy for Point Cloud Registration", IEEE Transactions on Evolutionary Computation (TEVC), 28(1), pp. 62 - 76, 2024.(IF=11.7) [Paper] [Code]
• Zedong Tang, Maoguo Gong, Yue Wu, Wenfeng Liu, Yu Xie, “Regularized Evolutionary Multitask Optimization: Learning to Intertask Transfer in Aligned Subspace", IEEE Transactions on Evolutionary Computation (TEVC), 25(2), pp. 262 - 276, 2021.(IF=11.7) [Paper] [Code]
• Yongzhe Yuan, Yue Wu(Corresponding Author), Xiaolong Fan, Maoguo Gong, Wenping Ma, Qiguang Miao, “EGST: Enhanced Geometric Structure Transformer for Point Cloud Registration", IEEE Transactions on Visualization and Computer Graphics (TVCG), 2023.(CCF A) [Paper] [Code]
• Zedong Tang, Maoguo Gong, Yue Wu, A. K. Qin, Kay Chen Tan, “A Multifactorial Optimization Framework Based on Adaptive Intertask Coordinate System", IEEE Transactions on Cybernetics (TCYB), 52(7), pp. 6745 - 6758, 2022.(IF=11.8) [Paper] [Code]
• Yue Wu, Jiaming Liu, Maoguo Gong, Qiguang Miao, Wenping Ma, Cai Xu, “Joint Semantic Segmentation using representations of LiDAR point clouds and camera images", Information Fusion (INFFUS), 108(12), pp. 1566-2535, 2024.(IF=14.7) [Paper] [Code]
• Yue Wu, Xidao Hu, Yue Zhang, Maoguo Gong, Wenping Ma, Qiguang Miao, “SACF-Net: Skip-Attention Based Correspondence Filtering Network for Point Cloud Registration", IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 33(8), pp. 3585 - 3595, 2023. [Paper] [Code]
• Yue Wu, Yue Zhang, Xiaolong Fan, Maoguo Gong, Qiguang Miao, Wenping Ma, “INENet: Inliers Estimation Network With Similarity Learning for Partial Overlapping Registration", IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 33(3), pp. 1413 - 1426, 2023. [Paper] [Code]
• Yongzhe Yuan, Yue Wu(Corresponding Author), Mingyu Yue, Maoguo Gong, Xiaolong Fan, Wenping Ma, Qiguang Miao, “Learning Discriminative Features via Multi-Hierarchical Mutual Information for Unsupervised Point Cloud Registration", IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2024. [Paper] [Code]
• Xiaolong Fan, Maoguo Gong, Yue Wu, Hao Li, “Maximizing Mutual Information Across Feature and Topology Views for Representing Graphs", IEEE Transactions on Knowledge and Data Engineering (TKDE), 35(10), pp. 10735 - 10747, 2023.(CCF A) [Paper] [Code]
• Xiaolong Fan, Maoguo Gong, Yue Wu, A. K. Qin, Yu Xie, “Propagation Enhanced Neural Message Passing for Graph Representation Learning", IEEE Transactions on Knowledge and Data Engineering (TKDE), 35(2), pp. 1952 - 1964, 2023.(CCF A) [Paper] [Code]
• Yue Wu, Jiaming Liu, Maoguo Gong, Peiran Gong, Xiaolong Fan, A. K. Qin, Qiguang Miao, Wenping Ma, “Self-Supervised Intra-Modal and Cross-Modal Contrastive Learning for Point Cloud Understanding", IEEE Transactions on Multimedia (TMM), 26, pp. 1626 - 1638, 2023. [Paper] [Code]
• Yue Wu, Jiaming Liu, Maoguo Gong, Zhixiao Liu, Qiguang Miao, Wenping Ma, “MPCT: Multiscale Point Cloud Transformer with a Residual Network", IEEE Transactions on Multimedia (TMM), 26, pp. 3505 - 3516, 2023. [Paper] [Code]
• Jiaming Liu, Yue Wu(Corresponding Author), Maoguo Gong, Zhixiao Liu, Qiguang Miao, Wenping Ma, “Inter-Modal Masked Autoencoder for Self-Supervised Learning on Point Clouds", IEEE Transactions on Multimedia (TMM), 26, pp. 3897-3908, 2023. [Paper] [Code]
• Wenping Ma, Jun Zhang, Yue Wu, Licheng Jiao; Hao Zhu; Wei Zhao, “A Novel Two-Step Registration Method for Remote Sensing Images Based on Deep and Local Features", IEEE Transactions on Geoscience and Remote Sensing (TGRS), 57(7), pp. 4834 - 4843, 2019. [Paper] [Code]
• Yongzhe Yuan, Yue Wu(Corresponding Author), Jiayi Lei, Congying Hu, Maoguo Gong, Xiaolong Fan, Wenping Ma, “Learning Compact Transformation Based on Dual Quaternion for Point Cloud Registration", IEEE Transactions on Instrumentation and Measurement (TIM), 2024. [Paper] [Code]
• Jiaming Liu, Yue Wu(Corresponding Author), Maoguo Gong; Qiguang Miao, Wenping Ma, Fei Xie, “Instance-Guided Point Cloud Single Object Tracking With Inception Transformer", IEEE Transactions on Instrumentation and Measurement (TIM), 2023. [Paper] [Code]
• Yue Wu, Yibo Liu, Maoguo Gong, Peiran Gong, Hao Li, Zedong Tang, Qiguang Miao, Wenping Ma, “Multi-View Point Cloud Registration Based on Evolutionary Multitasking With Bi-Channel Knowledge Sharing Mechanism", IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), 7(2), pp. 357 - 374, 2023. [Paper] [Code]
• 武越, 苑咏哲, 岳铭煜, 公茂果, 李豪, 张明阳, 马文萍, 苗启广, “点云配准中多维度信息融合的特征挖掘方法", 计算机研究与发展 , 59 (8), pp. 1732 - 1741, 2022. [Paper] [Code]
• 武越, 白壮飞, 公茂果, 曲博艺婷, 李豪, 张明阳, 马文萍, 苗启广, “遥感图像配准中的群智汇聚方法", 中国科学 , 53 (2), pp. 147 - 166, 2023. [Paper] [Code]

Conferences:

• Yue Wu, Xidao Hu, Yongzhe Yuan, Xiaolong Fan, Maoguo Gong, Hao Li, Mingyang Zhang, Qiguang Miao, Wenping Ma, “PointMC: Multi-instance Point Cloud Registration based on Maximal Cliques", International Conference on Machine Learning (ICML), 2024.(CCF A)
• Cai Xu, Jiajun Si, Ziyu Guan, Wei Zhao, Yue Wu, Xiyue Gao, “Reliable Conflictive Multi-View Learning", AAAI Conference on Artificial Intelligence (AAAI, Outstanding Paper), 2024.(CCF A) [Paper] [Code]
• Yongzhe Yuan, Yue Wu(Corresponding Author), Xiaolong Fan, Maoguo Gong, Qiguang Miao, Wenping Ma, “Inlier Confidence Calibration for Point Cloud Registration", IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.(CCF A) [Paper] [Code]
• Zedong Tang, Fenlong Jiang, Maoguo Gong, Hao Li, Yue Wu, Fan Yu, Zidong Wang, Min Wang, “SKFAC: Training Neural Networks with Faster Kronecker-factored Approximate Curvature", IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 13479-13487, 2021.(CCF A) [Paper] [Code]
• Jiaming Liu, Yue Wu(Corresponding Author), Maoguo Gong, Qiguang Miao, Wenping Ma, Cai Xu, Can Qin “M3SOT: Multi-Frame, Multi-Field, Multi-Space 3D Single Object Tracking", AAAI Conference on Artificial Intelligence (AAAI), pp. 3630-3638, 2024.(CCF A) [Paper] [Code]
• Xiaolong Fan, Maoguo Gong, Yue Wu, Zedong Tang, Jieyi Liu, “Neural Gaussian Similarity Modeling for Differential Graph Structure Learning", AAAI Conference on Artificial Intelligence (AAAI), 2024.(CCF A) [Paper] [Code]
• Jiaming Liu, Yue Wu(Corresponding Author), Maoguo Gong, Qiguang Miao, Wenping Ma, Cai Xu, “Exploring Dual Representations in Large-Scale Point Clouds: A Simple Weakly Supervised Semantic Segmentation Framework", ACM International Conference on Multimedia (ACM MM), pp. 2371-2380, 2023.(CCF A) [Paper] [Code]
• Cai Xu, Zehui Li, Ziyu Guan, Wei Zhao, Xiangyu Song, Yue Wu, Jianxin Li, “Unbalanced Multi-view Deep Learning", ACM International Conference on Multimedia (ACM MM), pp. 3051-3059, 2023.(CCF A) [Paper] [Code]

Team Members

PhD Students:

• PhD of 2022: Yongzhe Yuan(苑咏哲, 研究生国家奖学金), Yue Zhang(张越).
• PhD of 2023: Hangqi Ding(丁航奇, 研究生国家奖学金), Peiran Gong(公沛然, 研究生国家奖学金).
• PhD of 2024: Tengfei Xiao(肖腾飞).

Master Students:

• Master of 2022: Benhua Xiang(向本华, 研究生国家奖学金), Jinlong Sheng(绳金龙), Jiayi Lei(雷佳熠), Congying Hu(胡聪颖), Yifan Sun(孙逸帆), Zeyu Zhang(章泽宇).
• Master of 2023: Tianyu Bai(白天宇), Zhigang Gao(高志刚), Zhipeng Wang(王志鹏), Rongjie Guo(郭荣杰), Changhao Liu(刘昌昊), Hongfeng Wu(吴宏峰).
• Master of 2024: Jun Jiang(江君), Hao He(何昊), Shunjie Bi(毕顺杰), Yuhang Wang(王宇航), Feng Xiao(肖锋), Tao Peng(彭涛), JiaJun Yin(尹嘉骏), XiangJie He(何向杰), Yin Zhang(张胤).

Graduated Students:

• Master of 2021:
    Jiaming Liu(刘家铭, 研究生国家奖学金), 2021-2024, 上海交通大学在读博士
    Chuang Luo(罗闯), 2021-2024, 中国航空研究院631所
    Xidao Hu(胡西道, 研究生国家奖学金), 2021-2024, 中国移动通信有限公司西安研究院
    Jiaxin Xing(邢家鑫), 2021-2024, 小米科技有限责任公司
• Master of 2020:
    Yibo Liu(刘怡博, 研究生国家奖学金), 2020-2023, 北京旷视科技有限公司
    Qianlin Yao(姚乾林), 2020-2023, 深圳镭神智能系统有限公司
    Mingyu Yue(岳铭煜), 2020-2023, 国家电网英大泰和财产保险股份有限公司
    Yejian Cheng(程叶剑), 2020-2023, 中国航空研究院631所
    Jinsheng Liu(刘金生), 2020-2023, 华为技术有限公司
• Master of 2019:
    Zhenglei Xiao(肖郑磊), 中兴通讯股份有限公司
    Qiuyue Gao(高秋月), 北京百度网讯科技有限公司
    Zhuangfei Bai(白壮飞, 研究生国家奖学金), 华为技术有限公司
    Junwei Liu(刘君威, 研究生国家奖学金), 航天三院体系总体部
    Chenzhuo Zhu(朱晨卓), 华为技术有限公司
• Master of 2018:
    Hongyu Lu(陆洪玉), 2018-2021, 山东大学网络安全学院在读博士
    Hang Zhang(张航), 2018-2021, 中原银行股份有限公司
    Chenjie Wang(王晨杰, 优秀学生干部), 2018-2021, 北京字节跳动科技有限公司
    Peirong Zhang(张佩荣), 2018-2021, 中兴通讯股份有限公司
• Master of 2017:
    Guifeng Mu(慕贵峰), 2017-2020, 中国电信股份有限公司榆林分公司
    Simei Liu(刘思美), 2017-2020, 成都航昇机电有限责任公司

Enrollment Informations(招生信息):

I recruit 4-7 graduate students and 3-5 undergraduates annually in the field of Computer Science and Technology (top 0.1% in ESI). Students who are interested in artificial intelligence theory and applications, computational intelligence, 3D vision, machine learning, deep learning, and computer vision are welcome to contact and inquire. Additionally, my research team has several openings for graduate students. You are welcome to join us! (本人每年在计算机科学与技术领域招收 4-7 名研究生和 3-5 名本科生（ESI 排名前 0.1%）。欢迎对人工智能理论与应用、计算智能、三维视觉、机器学习、深度学习和计算机视觉感兴趣的学生联系和咨询。此外，我的研究团队还有几个研究生职位空缺。欢迎加入我们！)

Team Lab Research Profile(团队实验室科研情况简介)

Three-dimensional visual channel is one of the important ways for human brain to obtain information. Three-dimensional vision technology, which is centered on scene analysis and perception and understanding in three-dimensional space, is one of the important research directions of the new generation of artificial intelligence frontiers. We live in three-dimensional space, so how to intelligently perceive and explore the external environment has been a hot topic. Two-dimensional vision technology has achieved beyond human cognition with the help of powerful computer vision and deep learning algorithms, but three-dimensional vision still faces problems such as algorithmic modeling and environment dependence, and has been at the forefront of ongoing research. However, 3D information can reflect the state of objects and environment more realistically and is closer to human perception mode. In recent years, our lab team has been developing rapidly based on the Key Laboratory of Collaborative Intelligent Systems of the Ministry of Education, Xidian University. Based on the core technology of artificial intelligence, the team has launched scientific research in the field of 3D vision, focusing on solving its core problems such as scene analysis, semantic understanding, and collaborative optimization. In the process, the team has achieved a series of scientific research results with international influence. Our team publishes more than 20 papers every year in top international journals and conferences, such as IEEE TNNLS, IEEE TVCG, IEEE TEVC, AAAI, ACM MM, CVPR.(三维视觉通道是人类大脑获取信息的重要途径之一。以三维空间的场景分析与感知理解为核心的三维视觉技术，是新一代人工智能前沿的重要研究方向之一。我们生活在三维空间中，因此如何智能地感知和探索外部环境一直是个热点课题。二维视觉技术借助强大的计算机视觉和深度学习算法取得了超越人类认知的成就，但三维视觉仍然面临着算法建模和环境依赖等问题，一直处于正在研究的前沿。然而，三维信息能够更真实地反映物体和环境的状态，也更接近人类的感知模式。近年来，我们的实验室团队依托西安电子科技大学协同智能系统教育部重点实验室快速发展。以人工智能核心技术为基础，团队在三维视觉领域展开科学研究，着重解决其场景分析、语义理解、协同优化等核心问题。在此过程中，团队取得了一系列具有国际影响力的科研成果。我们的团队每年在IEEE TNNLS, IEEE TVCG, IEEE TEVC, AAAI, ACM MM, CVPR等国际顶级期刊和会议上发表论文20余篇。)

We Are Looking For Students Who(我们正在寻找具备以下条件的学生):

• Have a profound interest in Artificial Intelligence, enjoy conducting in-depth research, and are motivated by more than just the acquisition of a diploma or degree. (对人工智能有浓厚的兴趣，喜欢进行深入研究，其动机不仅仅是获得文凭或学位。)
• Are determined to pursue scientific research work after graduation. (决心在毕业后从事科研工作。)
• Exhibit a spirit of exploration and are not discouraged by challenges. (具有探索精神，面对挑战不气馁。)
• Possess strong English language skills. (具备较强的英语语言技能。)
• Physically and mentally healthy and active. (身心健康，积极向上。)
• Are mature thinkers with ideals and aspirations. (思想成熟，有理想和抱负。)

Requirements for Admission of PhD Students(招收博士生要求):

The MSc students in our team have all demonstrated strong research capabilities, and many of them aspire to be promoted to PhD in their second year. However, due to the scarcity and preciousness of PhD places, we have to face the reality that even outstanding students who have published as first author in top international journals or conferences may not be able to secure a PhD place in our team. For applicants from outside universities who are interested in joining our team to pursue a PhD degree, we have set a clear criterion: at least one paper published as the first author in international conferences or journals recognized as Class A by the China Computer Federation or in the first division by the Chinese Academy of Sciences. We have also set a requirement that all applicants from outside universities should have a PhD degree in a top international journal or conference. This requirement aims to ensure that our team's PhD cohort consists of members with outstanding research capabilities. If you meet the above criteria and are eager to join our research team, we encourage you to get in touch with us as soon as possible. We offer PhD students a generous package and a wealth of resources to support your academic development and professional growth. We are looking forward to your joining us to promote the development and progress of the 3D visualization field and explore the boundaries of knowledge! (我们团队的硕士生均展现出较强的研究能力，其中许多人都有志于在第二年晋升为博士生。然而，由于博士名额的稀缺和珍贵，我们不得不面对一个现实：即便是在国际顶级期刊或会议上以第一作者身份发表论文的优秀学生，也可能无法在我们团队获得博士生名额。对于有意加入我们团队攻读博士学位的外校申请者，我们设定了明确的标准：至少在CCF-A或中科院一区的国际学术会议或期刊上以第一作者身份发表过一篇论文。这一要求旨在确保我们团队的博士生队伍由科研能力卓越的成员组成。如果您符合上述条件，并且渴望加入我们的研究团队，我们鼓励您尽快与我们取得联系。我们为博士生提供了优厚的待遇和丰富的资源，以支持您的学术发展和职业成长。我们期待您的加入，共同推动三维视觉领域的发展和进步，探索知识的边界!)

How and When to Apply(如何以及何时联系):

• If you are ready to take your passion for computer science to the next level, please reach out to us for more information and to express your interest. Contact us at ywu[at]xidian.edu.cn to learn more about the application process and how you can become a part of our thriving research team. (如果您准备好将自己对计算机科学的热情提升到新的高度，请联系我们了解更多信息并表达您的兴趣。请通过ywu[at]xidian.edu.cn联系我们，了解更多申请流程以及如何成为我们蓬勃发展的研究团队的一员。)
• If you are eligible for guaranteed research, we recommend that you start contacting us in June to July of the second semester of your junior year. We will conduct an assessment in July-August to ensure that you will be able to join our research team. Please note that due to the large number of applicants each year, places for exempted postgraduate students are usually booked out by early August. Therefore, we strongly recommend that you contact us as early as possible to avoid missing out on valuable opportunities. For students interested in pursuing a PhD degree, we usually finalize the list of students who will enroll in September of the following year by November. Given the limited number of places available, we recommend that you prepare well in advance and contact us as early as possible to increase the success rate of your application. We look forward to your joining us and growing with you! (如果您符合保研条件，我们建议您在大三下学期的6至7月份开始与我们取得联系。我们将在7至8月份进行考核，以确保您能够顺利加入我们的研究团队。请注意，由于每年报考人数众多，免试研究生的名额通常在8月初就已经被预定完毕。因此，我们强烈建议您尽早与我们联系，以避免错过宝贵的机会。对于有意向攻读博士学位的学生，我们通常会在11月之前确定下一年9月入学的学生名单。鉴于名额有限，我们建议您提前做好准备，并尽早与我们联系，以提高您的申请成功率。我们期待您的加入，与你们共同成长！)

Work Environment(工作环境):

Our lab is dedicated to creating a superior academic environment with ample computing resources for each member. We have a number of high-performance graphics servers, including RTX 4090 and RTX 3090 and other advanced equipment, ensuring that each team member can use two high-performance graphics cards per person. We are confident that these computing resources will provide you with strong support for your research and study, and help you make excellent progress on your path of academic exploration. (我们的实验室致力于打造一个优越的学术环境，为每位成员提供充足的计算资源。我们拥有多台高性能显卡服务器，包括RTX 4090和RTX 3090等先进设备，确保每位团队成员都能够人均使用两块高性能显卡。我们相信，这些计算资源能够为您的研究和学习提供强大的支持，助力您在学术探索的道路上取得优异进步!)