# Xiao Wang(王啸)

Associate Professor

School of Software, Beihang University, Beijing, China

Email: xiaowang[AT]bupt[DOT]edu[DOT]cn

Brief Bio - News - Experiences - Publications


# Brief Bio

He is an associate professor at Beihang University, China. Prior to BUAA, he was an associate professor at Beijing University of Posts and Telecommunications. His research interests are graph neural networks, data mining and machine learning. He was a postdoc in the Department of Computer Science and Technology at Tsinghua University working with Professor Shiqiang Yang and Professor Peng Cui. He got the Ph.D. in the School of Computer Science and Technology at Tianjin University under the supervision of Prof. Xiaochun Cao in 2016. From Nov. 2014 to Nov. 2015, he visited Prof. Weixiong Zhang's group at Washington University in St. Louis as a visiting student. He has published 90 peer reviewed papers in top venues (e.g., KDD, WWW, NeurIPS, AAAI, IJCAI, IEEE TKDE). One paper gets the WWW 2021 Best Paper Awards Nomination, and one paper gets ICDM 2021 Best Student Paper Awards Runner-up. He obtains the ACM China Rising Star Nomination Awards and is selected to the Star Track Program in MSRA in 2020. He is the CCF Senior Member and is recognized as the 2022 AI 2000 Most Influential Scholar Honorable Mention in AAAI/IJCAI by AMiner.


# News

[12/22] One paper was accepted by IEEE TNNLS.

[12/22] One paper was accepted by AAAI 2023.

[11/22] Accepted to serve as PC for CVPR 2023.

[10/22] Accepted to serve as PC for WWW 2023.

[09/22] Three papers were accepted by NeurIPS 2022.

[09/22] I received 2022 the world artificial intelligence conference youth outstanding paper nomination award.

[08/22] The Chinese version of our book "heterogeneous graph representation learning and applications" has been published

[08/22] One paper was accepted by KAIS.

[07/22] Accepted to serve as SPC for AAAI 2023.

[06/22] One paper was accepted by CIKM 2022.

[06/22] Accepted to serve as PC member for WSDM 2023.

[04/22] One paper was accepted by IJCAI 2022.

[03/22] Two papers were accepted by SIGIR 2022.

[03/22] I'm honored to be recognized as the 2022 AI 2000 Most Influential Scholar Honorable Mention in AAAI/IJCAI by AMiner.

[03/22] Accepted to serve as PC member for NeurIPS 2022.

[03/22] Accepted to serve as PC member for ICDM 2022.

[03/22] Accepted to serve as PC member for ECCV 2022.

[01/22] Three papers were accepted by The WebConference 2022. Congratulations to all the collaborators!

[12/21] One paper on debiased graph neural networks was accepted by IEEE TNNLS. Congratulations to all the collaborators!

[12/21] Accepted to serve as PC member for ICME 2022.

[12/21] Accepted to serve as PC member for ICML 2022.

[12/21] Two papers on graph augmentations for GNNs and robust heterogeneous GNNs were accepted by AAAI 2022. Congratulations to all the collaborators!

[11/21] I received the ICDM 2021 Best Student Paper Runner Up.

[11/21] Accepted to serve as PC member for KDD 2022.

[10/21] Accepted to serve as SPC for WWW 2022.

[10/21] Accepted to serve as PC member for SDM 2022.

[09/21] Accepted to serve as PC member for CVPR 2022.

[09/21] Two papers on trustworthy GNNs and heterophilic GNNs were accepted by NeurIPS 2021. Congratulations to all the collaborators!

[09/21] I was selected to be a Senior Member of CCF.

[08/21] One paper on text-rich network representation learning was accepted by ICDM 2021. Congratulations to all the collaborators!

[04/20] We release an open-source toolkit for Heterogeneous Information Network Embedding (OpenHINE (opens new window)).


# Experiences

  • Visiting Student, Department of Computer Science and Engineering, Washington University in St. Louis, Missouri, USA, November, 2014- December, 2015
  • Visiting Student, CNSA Center for Spacebome Remote Sensing Demonstration, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China, March, 2010- April, 2012

# Books/Chapters

  • 石川, 王啸, 胡琳梅. 数据科学导论. 清华大学出版社. 2021. [Link (opens new window)]
  • Chuan Shi, Xiao Wang, Philip S. Yu. Heterogeneous Graph Representation Learning and Applications. Springer. 2022. [Link (opens new window)].
  • 石川,王啸,俞士纶(Philip S. Yu). 异质图表示学习与应用. 机械工业出版社. 2022
  • Peng Cui, Lingfei Wu, Jian Pei, Liang Zhao, Xiao Wang. Chapter 2: Graph Representation Learning [Link (opens new window)]. In Graph Neural Networks: Foundations, Frontiers, and Applications [Link (opens new window)]. Springer. 2022.
  • Chuan Shi, Xiao Wang, Cheng Yang. Advances in Graph Neural Networks. Springer. 978-3-031-16173-5. 2022.

# Publications [Google Scholar (opens new window)]

  • 2023

[C1] Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi. Directed acyclic graph structure learning from dynamic graphs. AAAI 2023. (CCF-A)

[J1] Yanbei Liu, Lianxi Fan, Xiao Wang, Zhitao Xiao, Shuai Ma, Yanwei Pang, Jerry Chun-Wei Lin. HGBER: Heterogeneous Graph Neural Network with Bidirectional Encoding Representation. IEEE TNNLS.

  • # 2022

[C1] Deyu Bo, Binbin Hu, Xiao Wang, Zhiqiang Zhang, Chuan Shi, Jun Zhou. Regularizing graph neural networks via consistency-diversity graph augmentations. AAAI 2022. (CCF-A)

[C2] Mengmei Zhang, Xiao Wang, Meiqi Zhu, Chuan Shi, Zhiqiang Zhang, Jun Zhou. Robust heterogeneous graph neural networks against adversarial attacks. AAAI 2022. (CCF-A)

[C3] Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi. Compact Graph Structure Learning via Mutual Information Compression. WWW 2022. (CCF-A)

[C4] Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou. Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift. WWW 2022. (CCF-A)

[C5] Yugang Ji, Guanyi Chu, Xiao Wang, Chuan Shi, Jianan Zhao. Prohibited Item Detection via Risk Graph Structure Learning. WWW 2022. (CCF-A)

[C6] Yiding Zhang, Chaozhuo Li, Xing Xie, Xiao Wang, Chuan Shi, Yuming Liu, Hao Sun, Liangjie Zhang, Weiwei Deng, Qi Zhang. Geometric disentangled collaborative filtering. SIGIR 2022. (CCF-A)

[C7] Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi. Space4HGNN: A novel, modularized and reproducible platform to evaluate heterogeneous graph neural network. SIGIR 2022. (CCF-A)

[C8] Shuyun Gu, Xiao Wang, Chuan Shi, Ding Xiao. Self-supervised graph neural networks for multi-behavior recommendation. IJCAI 2022. (CCF-A)

[C9] Hui Han, Tianyu Zhao, Cheng Yang, Hongyi Zhang, Yaoqi Liu, Xiao Wang, Chuan Shi. OpenHGNN: An open-source toolkit for heterogeneous graph neural networks. CIKM 2022.

[C10] Nian Liu, Xiao Wang*, Deyu Bo, Chuan Shi, Jian Pei. Revisiting graph contrastive learning from the perspective of graph spectrum. NeurIPS 2022. (CCF-A)

[C11] Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang. Debiasing graph neural networks via learning disentangled causal substructure. NeurIPS 2022. (CCF-A)

[C12] Ruijia Wang, Xiao Wang*, Chuan Shi, Le Song. Uncovering the structural fairness in graph contrastive learning. NeurIPS 2022. (CCF-A)

[J1] Shaohua Fan, Xiao Wang, Chuan Shi, Kun Kuang, Nian Liu, Bai Wang. Debiased graph neural networks with agnostic label selection bias. IEEE TNNLS.

[J2] Shaohua Fan, Xiao Wang, Chuan Shi, Peng Cui, Bai Wang. Generalizing graph neural networks on out-of-distribution graphs. arXiv:2111.10657 (opens new window)

[J3] Zhizhi Yu, Di Jin, Ziyang Liu, Dongxiao He, Xiao Wang, Hanghang Tong, Jiawei Han. Embedding text-rich graph neural networks with sequence and topical semantic structures. KAIS.

  • # 2021

[C1] Jianan Zhao, Xiao Wang*, Chuan Shi, Binbin Hu, Guojie Song, Yanfang Ye. Heterogeneous graph structure learning for graph neural networks. AAAI 2021. (CCF-A)

[C2] Deyu Bo, Xiao Wang, Chuan Shi, Huawei Shen. Beyond Low-frequency Information in Graph Convolutional Networks. AAAI 2021. (CCF-A)

[C3] Houye Ji, Junxiong Zhu, Xiao Wang,Chuan Shi, Bai Wang, Xiaoye Tan, Yanghua Li, Shaojian He. Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce. AAAI 2021. (CCF-A)

[C4] Yiding Zhang, Xiao Wang, Chuan Shi, Nian Liu, Guojie Song. Lorentzian Graph Convolutional Neural Networks. WWW 2021. (CCF-A)

[C5] Meiqi Zhu, Xiao Wang*, Chuan Shi, Houye Ji, Peng Cui. Interpreting and Unifying Graph Neural Networks with An Optimization Framework. WWW 2021. (CCF-A) Best Paper Awards Nomination! Most influential papers in WWW 2020 (TOP 15) by PaperDigest

[C6] Ruijia Wang, Shuai Mou, Xiao Wang*, Wanpeng Xiao, Qi Ju, Chuan Shi, Xing Xie. Graph Structure Estimation Neural Networks. WWW 2021. (CCF-A)

[C7] Houye Ji, Junxiong Zhu, Chuan Shi, Xiao Wang, Bai Wang, Chaoyu Zhang, Zixuan Zhu, Feng Zhang, Yanghua Li. Large-scale Comb-K Recommendation. WWW 2021. (CCF-A)

[C8] Hong Huang, Ruize Shi, Wei Zhou, Xiao Wang*, Hai Jin, Xiaoming Fu. Temporal heterogeneous information network embedding. IJCAI 2021. (CCF-A)

[C9] Guanyi Chu, Xiao Wang, Chuan Shi, Xunqiang Jiang. CuCo: graph representation with curriculum contrastive learning. IJCAI 2021. (CCF-A)

[C10] Xiao Wang, Nian Liu, Hui Han, Chuan Shi. Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning. KDD 2021. (CCF-A)

[C11] Yugang Ji, Chuan Shi, Xiao Wang. Prohibited Item Detection on Heterogeneous Risk Graphs. CIKM 2021.

[C12] Zhizhi Yu, Di Jin, Ziyang Liu, Dongxiao He, Xiao Wang*, Hanghang Tong, Jiawei Han. AS-GCN: Adaptive semantic architecture of graph convolutional networks for text-rich networks. ICDM 2021. Best Student Paper Runner Up!

[C13] Xiao Wang, Hongrui Liu, Chuan Shi, Cheng Yang. Be confident! Towards trustworthy graph neural networks via confidence calibration. NeurIPS 2021. (CCF-A)

[C14] Di Jin, Zhizhi Yu, Cuiying Huo, Rui Wang, Xiao Wang*, Dongxiao He, Jiawei Han. Universal graph convolutional networks. NeurIPS 2021. (CCF-A)

[J1] Houye Ji, Xiao Wang, Chuan Shi, Bai Wang, Philip S. Yu. Heterogeneous graph propagation network. IEEE TKDE. (CCF-A)

[J2] 石川,王睿嘉,王啸*. 异质信息网络分析与应用综述. 软件学报.

[J3] Yiding Zhang, Xiao Wang, Chuan Shi, Xunqiang Jiang, Yanfang Ye. Hyperbolic graph attention network. IEEE TBD.

[J4] Yiding Zhang, Xiao Wang, Nian Liu, Chuan Shi. Embedding heterogeneous information network in hyperbolic spaces. ACM TKDD.

[J5] Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye, Philip S. Yu. A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources. IEEE TBD.

[J6] Ruijia Wang, Chuan Shi, Tianyu Zhao, Xiao Wang, Yanfang Ye. Heterogeneous information network embedding with adversarial disentangler. IEEE TKDE. (CCF-A)

  • # 2020

[C1] Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, Jian Pei. AM-GCN: Adaptive Multi-channel Graph Convolutional Networks. KDD 2020. (CCF-A) Most influential papers in KDD 2020 (TOP 15) by PaperDigest

[C2] Xiao Wang, Ruijia Wang, Chuan Shi, Guojie Song, Qingyong Li. Multi-component graph convolutional collaborative filtering. AAAI 2020. (CCF-A)

[C3] Yanbei Liu, Xiao Wang*, Shu Wu, Zhitao Xiao. Independence promoted graph disentangled networks. AAAI 2020. (CCF-A)

[C4] Xiao Wang, Shaohua Fan, Kuang Kun, Chuan Shi, Jiawei Liu, Bai Wang. Decorrelated clustering with data selection bias. IJCAI 2020. (CCF-A)

[C5] Jianan Zhao, Xiao Wang*, Chuan Shi, Zekuan Liu, Yanfang Ye. Network Schema Preserving Heterogeneous Information Network Embedding. IJCAI 2020. (CCF-A)

[C6] Hong Huang, Zixuan Fang, Xiao Wang*, Youshan Miao, Hai Jin. Motif-preserving temporal network embedding. IJCAI 2020. (CCF-A)

[C7] Deyu Bo, Xiao Wang*, Chuan Shi, Meiqi Zhu, Emiao Lu, Peng Cui. Structural Deep Clustering Network. WWW 2020. (CCF-A) Most influential papers in WWW 2020 (TOP 15) by PaperDigest

[C8] Shaohua Fan, Xiao Wang, Chuan Shi, Emiao Lu, Ken Lin, Bai Wang. One2Multi Graph Autoencoder for Multi-view Graph Clustering. WWW 2020. (CCF-A)

[C9] Mengmei Zhang, Linmei Hu, Chuan Shi, Xiao Wang. Adversarial Label-Flipping Attack and Defense for Graph Neural Networks. ICDM 2020. (CCF-B)

[J1] Xiao Wang, Yuanfu Lu, Chuan Shi, Ruijia Wang, Peng Cui, Shuai Mou. Dynamic Heterogeneous Information Network Embedding with Meta-path based Proximity. IEEE TKDE 2020. (CCF-A)

  • 2019

[C1] Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Peng Cui, Philip S. Yu, Yanfang Ye. Heterogeneous Graph Attention Network. WWW 2019. (CCF-A) [code (opens new window)] Most influential papers in WWW 2019 (TOP 15) by PaperDigest. 2022 The world artificial intelligence conference youth outstanding paper nomination award.

[C2] Xiao Wang, Yiding Zhang, Chuan Shi. Hyperbolic heterogeneous information network embedding. AAAI 2019. (CCF-A) [code (opens new window)]

[C3] Yuanfu Lu, Xiao Wang, Chuan Shi, Philip S. Yu, Yanfang Ye. Temporal network embedding with micro- and macro-dynamics. CIKM 2019. (CCF-B)

[J1] Ping Xuan, Tonghui Shen, Xiao Wang, Tiangang Zhang, Weixiong Zhang. Inferring disease-associated microRNAs in heterogeneous networks with node attributes. *IEEE/ACM Transactions on Computational Biology and Bioinformatics. *(CCF-C)

[J2] Ping Xuan, Yangkun Cao, Tiangang Zhang, Xiao Wang, Shuxiang Pan, Tonghui Shen. Drug repositioning through integration of prior knowledge and projections of drugs and diseases. Bioinformatics. (CCF-B)

[J3] Ping Xuan, Hao Sun, Xiao Wang*, Tiangang Zhang, Shuxiang Pan. Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks. International Journal of Molecular Sciences.

[J4] Liang Yang, Yuexue Wang, Junhua Gu, Xiaochun Cao, Xiao Wang*, Di Jin, Guiguang Ding, Jungong Han, Weixiong Zhang. Autonomous Semantic Community Detection via Adaptively Weighted Low-rank Approximation. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP). (CCF-B)

[J5] Chuan Shi, Xiaotian Han, Li Song, Xiao Wang*, Senzhang Wang, Junping Du, Philip S. Yu. Deep collaborative filtering with multi-aspect information in heterogeneous networks. IEEE TKDE. (CCF-A)

  • 2018

[C1] Xiao Wang, Ziwei Zhang, Jing Wang, Peng Cui, Shiqiang Yang. Power-law distribution aware trust prediction. IJCAI 2018. (CCF-A) [code (opens new window)]

[C2] Ke Tu, Peng Cui, Xiao Wang*, Fei Wang, Wenwu Zhu. Structural deep embedding for hyper-networks. AAAI 2018. (CCF-A) [code (opens new window)]

[C3] Ziwei Zhang, Peng Cui, Jian Pei, Xiao Wang*, Wenwu Zhu. TIMERS: error-bounded SVD restart on dynamic networks. AAAI 2018. (CCF-A) [code (opens new window)]

[C4] Jing Wang, Feng Tian, Weiwei Liu, Xiao Wang*, Wenjie Zhang, Kenji Yamanishi. Ranking Preserving Nonnegative Matrix Factorization. IJCAI 2018. (CCF-A)

[C5] Ziwei Zhang, Peng Cui, Xiao Wang, Jian Pei, Xuanrong Yao and Wenwu Zhu. Arbitrary-Order Proximity Preserved Network Embedding. KDD 2018. (CCF-A) [code (opens new window)]

[C6] Ke Tu, Peng Cui, Xiao Wang, Philip S. Yu and Wenwu Zhu. Deep Recursive Network Embedding with Regular Equivalence. KDD 2018. (CCF-A) [code (opens new window)]

[C7] Jianxin Ma, Peng Cui, Xiao Wang and Wenwu Zhu. Hierarchical Taxonomy Aware Network Embedding. KDD 2018. (CCF-A) [code (opens new window)]

[C8] Shaohua Fan, Chuan Shi, Xiao Wang. Abnormal event detection via heterogeneous information network embedding. CIKM 2018. (CCF-B) [code (opens new window)]

[C9] Ziwei Zhang, Peng Cui, Haoyang Li, Xiao Wang, Wenwu Zhu. Billion-scale Network Embedding with Iterative Random Projection. ICDM 2018. (CCF-B) [code (opens new window)]

[C10] Hongcui Wang, Erwei Wang, Di Jin, Xiao Wang, etc. Edge content enhanced network embedding. ICTAI 2018. (CCF-C)

[C11] Jing Hu, Changqing Zhang, Xiao Wang, Pengfei Zhu, Zheng Wang and Qinghua Hu. Latent Subspace Representation For Multiclass Classification. PRICAI 2018. (CCF-C)

[J1] Peng Cui, Xiao Wang*, Jian Pei, Wenwu Zhu. A survey on network embedding. IEEE TKDE . (CCF-A) ESI highly cited paper!

[J2] Yanbei Liu, Kaihua Liu, Changqing Zhang, Xiao Wang, Shaona Wang and Zhitao Xiao. Entropy-based active sparse subspace clustering. Multimedia Tools and Applications. (JCR-3)

  • 2017

[C1] Xiao Wang, Peng Cui, Jing Wang, Jian Pei, Wenwu Zhu, Shiqiang Yang. Community Preserving Network Embedding. The 31st AAAI Conference on Artificial Intelligence (AAAI-17). [CODE (opens new window)] (CCF-A) Most influential papers in AAAI 2017 (TOP 15) by PaperDigest

[C2] Jing Wang, Feng Tian, Xiao Wang*, Chang Hong Liu, Hongchuan Yu, Liang Yang. Multi-Component Nonnegative Matrix Factorization. The 26th International Joint Conference on Artificial Intelligence (IJCAI-17). (CCF-A)

[C3] Jing Wang, Feng Tian, Chang Hong Liu, Hongchuan Yu, Xiao Wang*, Xianchao Tang. Robust Nonnegative Matrix Factorization with Ordered Structure Constraints. The 2017 International Joint Conference on Neural Networks (IJCNN 2017). Oral. (CCF-C)

[J1] Xianchao Tang, Tao Xu, Xia Feng, Guoqing Yang, Jing Wang, Qiannan Li, Yanbei Liu, Xiao Wang*. Learning Community Structures: Global and Local Perspectives. Neurocomputing, 2017. (JCR-2)

[J2] Yingli Zhong, Ping Xuan, Xiao Wang, Tiangang Zhang, Jianzhong Li, Yong Liu, Weixiong Zhang. A non-negative matrix factorization based method for predicting disease-associated miRNAs in miRNA-disease bilayer network. Bioinformatics, 2017. (CCF-B)

[J3] Jing Wang, Feng Tian, Chang Hong Liu, Hongchu an Yu, Kun Zhan, Xiao Wang*. Diverse multi-view nonnegative matrix factorization for data representation. IEEE Transactions on Cybernetics, 2017. (JCR-1)

  • 2016

[C1] Xiao Wang, Di Jin, Xiaochun Cao, Liang Yang, Weixiong Zhang. Semantic community detection in large attribute networks. The Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16). [CODE (opens new window)] (CCF-A)

[C2] Jing Wang, Xiao Wang, Feng Tian, Chang Hong Liu, Hongchuan Yu, Yanbei Liu. Adaptive Multi-View Semi-Supervised Nonnegative Matrix Factorization. The 23rd International Conference on Neural Information Processing (ICONIP 2016). (CCF-C)

[C3] Liang Yang, Xiaochun Cao, Dongxiao He, Chuan Wang, Xiao Wang, Weixiong Zhang. Modularity based community detection with deep learning. The 25th International Joint Conference on Artificial Intelligence (IJCAI-16). (CCF-A)

[J1] Jing Wang, Xiao Wang, Feng Tian, Chang Hong Liu, Hongchuan Yu. Constrained Low-Rank Representation for Robust Subspace Clustering. IEEE Transactions on Cybernetics, 2016. (JCR-1)

[J2] Yanbei Liu, Kaihua Liu, Changqing Zhang, Jing Wang, Xiao Wang*. Unsupervised Feature Selection via Diversity-induced Self-representation. Neurocomputing 2016. [CODE (opens new window)] (JCR-2)

[J3] Xianchao Tang, Guoqing Yang, Tao Xu, Xia Feng, Xiao Wang*, Qiannan Li, Yanbei Liu. Link community detection by nonnegative matrix factorization with multi-step similarities. Modern Physics Letters B. 2016.

  • Before 2015

[C1] Jing Wang, Feng Tian, Changhong Liu, Xiao Wang. Robust Semi-supervised Nonnegative Matrix Factorization. The 2015 International Joint Conference on Neural Networks (IJCNN 2015). Accepted as Oral. (CCF-C)

[C2] Xiaochun Cao, Xiao Wang, Di Jin, Yixin Cao, Dongxiao He. The (un)supervised detection of overlapping communities as well as hubs and outliers via (Bayesian) NMF [C]. The 23th International World Wide Web Conference (WWW2014), poster.

[J1] Xiaochun Cao, Xiao Wang, Di Jin, Yixin Cao, Dongxiao He. Identifying overlapping communities as well as hubs and outliers via nonnegative matrix factorization [J]. Scientific Reports 2013, 3, 2993[CODE (opens new window)] (JCR-2)

[J2] Liang Yang, Xiaochun Cao, Di Jin, Xiao Wang, Dan Meng. A Unified Semi-Supervised Community Detection Framework Using Latent Space Graph Regularization. IEEE Trans. on Cybernetics, 2014 (JCR-1)

[J3] Xiaochun Cao, Xiao Wang*, Di Jin, Xiaojie Guo, Xianchao Tang. A Stochastic Model for Detecting Overlapping and Hierarchical Community Structure. PLOS ONE 2015.

[J4] Liang Yang, Di Jin, Xiao Wang, Xiaochun Cao. Active Link Selection for Efficient Semi-supervised Community Detection. Scientific Reports 2015. (JCR-2)

[J5] Xiao Wang, Xiaochun Cao, Di Jin, Yixin Cao, Dongxiao He. The (un)supervsied NMF methods for discovering overlapping communities as well as hubs and outliers in networks. Physica A: Statistical Mechanics and its Applications. 2015. This is the journal extension version of our WWW2014 paper.

*Corresponding author/Equal contribution.


# Honors Awarded

  • 2022 The world artificial intelligence conference youth outstanding paper nomination award
  • 2022 AI 2000 Most Influential Scholar Honorable Mention in AAAI/IJCAI
  • 2021 ACM China Rising Star Award Nomination (3 nominees in China)
  • 2021 ICDM 2021 Best Student Paper Runner-up
  • 2021 WWW 2021 Best Paper Awards Nomination

# Professional Experiences

  • Reviewer for Journals:

    IEEE TPAMI, IEEE TKDE, IEEE TCybernetics, IEEE TNNLS, IEEE TIP, IEEE TBD, IEEE TSP, IEEE Transactions on Network Science and Engineering, ACM TOIS, ACM TIST, Journal of Artificial Intelligence Research (JAIR), Information Sciences, Neurocomputing, World Wide Web Journal, Neural Networks, PLOS ONE, Future Generation Computer Systems, MultiMedia Tools and Applications, Frontiers of Computer Science, Computer Science (in Chinese), Information Processing & Management

  • SPC/PC for Conferences (After 2018):

    • PC: AAAI 2018, 2019, 2020; CIKM 2019; IJCAI 2019, 2020, 2022, 2023; KDD 2019, 2020, 2021, 2022; PAKDD 2019, 2020, 2021, 2023; ACM MM 2019, 2020, 2021; ECAI 2020; WWW 2021, 2023; ICDM 2020, 2021, 2022; ICML 2021, 2022; ICCV 2021; PRICAI 2021; WSDM 2022, 2023; CVPR 2022, 2023; SDM 2022; ICME 2022; ECCV 2022; NeurIPS 2022
    • SPC: AAAI 2021, 2022, 2023; IJCAI 2021; WWW 2022