Wu-Jun LI (Resume in Chinese)
Professor, PhD

National Key Laboratory for Novel Software Technology
Department of Computer Science and Technology
Nanjing University
163 Xianlin Avenue, Qixia District, Nanjing, 210023, P.R.China

Office: Room 402, Computer Science Building

Email: liwujun at nju.edu.cn

News


  • [Jun 10, 2023] 招收2024年入学的博士生、直博生和硕士生。请将个人简历和成绩单发送到 liwujun@nju.edu.cn。

  • [May 25, 2022] 长期招收本校计算机、数学、电子相关专业的大二、大三本科生进组实习,要求成绩优异。请将个人简历和成绩单发送到 liwujun@nju.edu.cn。

  • [Apr 20, 2021] Wu-Jun Li has been recognized as the AI 2000 Most Influential Scholar (李武军老师获得 AI 2000人工智能全球最具影响力学者奖)

Biography

Wu-Jun LI is currently a full professor at the Department of Computer Science and Technology, Nanjing University.

From 2010 to 2013, he was a faculty member of the Department of Computer Science and Engineering at Shanghai Jiao Tong University (SJTU) .

He received his PhD degree from the Department of Computer Science and Engineering, HKUST in 2010, under the supervision of Prof. Dit-Yan Yeung.

Before that, he received his M.Eng. degree and B.Sc. degree from the Department of Computer Science and Technology, Nanjing University in 2006 and 2003, respectively.

Research Interests

·        Artificial Intelligence

·        Machine Learning

·        Big Data  

·        Intelligent Medicine

·        AI for Science

Students

·       PhD Students:

Kai-Lang Yao, Xiao Ma, Chu-Xiao Zuo, Jun Li, Yi-Rui Yang, Yan-Shuo Liang, Yu-Hao Huang, Chang-Wei Shi, Jin Han, Ke Wu

·       Master Students:

Shan-Liang Chen, Hao Lin, Kun Wang, Yu Xia, Wen-Pu Cai, Jian Lin, Jin-Dong Zhou, Zhi-Jun Jia, Yu-Ying Liu, Neng Lu, Huan-Yi Su

·       Undergraduate Students:

Cheng Chen, Jia-Hao Zhu

·       Alumni

Teaching

·       Courses in Nanjing University:

Data Structures [for UG students, Spring 2014, Fall 2015, Fall 2016, Fall 2017, Spring 2018, Fall 2019, Fall 2020, Spring 2021, Fall 2022, Fall 2023]

Big Data Analytics [for part-time PG students, Fall 2017, Fall 2018, Fall 2019]

·       Former courses in SJTU:

Web Search and Mining [for PG students, Fall 2010, Fall 2011, Fall 2012]

Mining Massive Datasets [for UG students, Spring 2011, Spring 2012, Spring 2013]

Information Retrieval in Practice [for UG students, Spring 2012]

Big Data Processing in Practice [for UG students, Fall 2012]


Selected Publications (* indicates students under my supervision) [Publication list in DBLP]

Technical Report:

  • UniAP: Unifying Inter- and Intra-Layer Automatic Parallelism by Mixed Integer Quadratic Programming.
    Hao Lin*, Ke Wu*, Jun Li*
    , Wu-Jun Li.
    [arXiv version]


  • FedREP: A Byzantine-Robust, Communication-Efficient and Privacy-Preserving Framework for Federated Learning.
    Yi-Rui Yang*, Kun Wang*, Wu-Jun Li.
    [arXiv version]


  • GNNFormer: A Graph-based Framework for Cytopathology Report Generation.
    Yang-Fan Zhou*, Kai-Lang Yao*, Wu-Jun Li.
    [arXiv version]

  • Global Momentum Compression for Sparse Communication in Distributed SGD.
    Shen-Yi Zhao*, Yin-Peng Xie*, Hao Gao*, Wu-Jun Li.
    [arXiv version]


  • , Hao Gao*, Wu-Jun Li.
    [arXiv version]

  • TOMA: Topological Map Abstraction for Reinforcement Learning.
    Zhao-Heng Yin*, Wu-Jun Li.
    [arXiv version]

  • , Shen-Yi Zhao*, Wu-Jun Li.
    [arXiv version]


  • , Ming-Wei Li*, Wu-Jun Li.
    [arXiv version]


Published Papers:
  • NEWInterference-Free Low-Rank Adaptation for Continual Learning.
    Yan-Shuo Liang*, Wu-Jun Li.

    Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
    [pdf]

  • NEWOn the Effect of Batch Size in Byzantine-Robust Distributed Learning.
    Yi-Rui Yang*, Chang-Wei Shi*, Wu-Jun Li.
    The Twelfth International Conference on Learning Representations (ICLR), 2024.
    [pdf]

  • NEWWeighted Online Decision Transformer with Episodic Memory for Offline-to-Online Reinforcement Learning.
    Xiao Ma*, Wu-Jun Li.
    Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2024.
    [pdf]

  • NEWAsymmetric Learning for Graph Neural Network based Link Prediction.
    Kai-Lang Yao*, Wu-Jun Li.
    ACM Transactions on Knowledge Discovery from Data (TKDD), 2024.
    [pdf]

  • NEWAdvTTS: Adversarial Text-to-Speech Synthesis Attack on Speaker Identification Systems.
    Chu-Xiao Zuo*, Zhi-Jun Jia*, Wu-Jun Li.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024.
    [pdf]

  • Stochastic Normalized Gradient Descent with Momentum for Large-Batch Training.
    Shen-Yi Zhao*, Chang-Wei Shi*, Yin-Peng Xie*, Wu-Jun Li.
    SCIENCE CHINA Information Sciences (SCIS), 2023.
    [pdf]


  • Loss Decoupling for Task-Agnostic Continual Learning.
    Yan-Shuo Liang*, Wu-Jun Li.
    Advances in Neural Information Processing Systems (NeurIPS), 2023.
    [pdf]

  • Adaptive Plasticity Improvement for Continual Learning.
    Yan-Shuo Liang*, Wu-Jun Li.
    Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
    [pdf]

  • Buffered Asynchronous SGD for Byzantine Learning.
    Yi-Rui Yang*, Wu-Jun Li.
    Journal of Machine Learning Research (JMLR), 2023.
    [pdf]


  • State-based Episodic Memory for Multi-Agent Reinforcement Learning.
    Xiao Ma*, Wu-Jun Li.
    Machine Learning (MLJ), 2023.
    [pdf]


  • Re-quantization based Binary Graph Networks.
    Kai-Lang Yao*, Wu-Jun Li.
    SCIENCE CHINA Information Sciences (SCIS), 2023.
    [pdf]

  • Context Sketching for Memory-efficient Graph Representation Learning.
    Kai-Lang Yao*, Wu-Jun Li.
    Proceedings of the International Conference on Data Mining (ICDM), 2023.
    [pdf]


  • Fooling Speaker Identification Systems with Adversarial Background Music.
    Chu-Xiao Zuo*, Jia-Yi Leng*, Wu-Jun Li.
    Proceedings of the Annual Conference of the International Speech Communication Association (INTERSPEECH), 2023.
    [pdf]

  • A real-time interpretable artificial intelligence model for the cholangioscopic diagnosis of malignant biliary stricture.
    Xiang Zhang, Dehua Tang, Jindong Zhou*, Muhan Ni, Peng Yan, Zhenyu Zhang, Tao Yu, Qiang Zhan, Yonghua Shen, Lin Zhou, Ruhua Zheng, Xiaoping Zou, Bin Zhang#, Wu-Jun Li#, Lei Wang#.
    Gastrointestinal Endoscopy (GIE), 2023. [# denotes co-corresponding author]
    [pdf]


  • Hardware Computation Graph for DNN Accelerator Design Automation without Inter-PU Templates
    Jun Li*, Wei Wang, Wu-Jun Li.
    Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design (ICCAD),
    2022.
    [pdf]

  • Cross Domain Robot Imitation with Invariant Representation.
    Zhao-Heng Yin, Lingfeng Sun, Hengbo Ma, Masayoshi Tomizuka, Wu-Jun Li.
    Proceedings of the IEEE International Conference on Robotics and Automation (ICRA),
    2022.
    [pdf]

  • Speaker-Specific Utterance Ensemble based Transfer Attack on Speaker Identification.
    Chu-Xiao Zuo*, Jia-Yi Leng*, Wu-Jun Li.

    Proceedings of the Annual Conference of the International Speech Communication Association (INTERSPEECH),
    2022.
    [pdf]

  • A deep learning-based segmentation system for rapid onsite cytologic pathology evaluation of pancreatic masses: A retrospective, multicenter, diagnostic study.
    Song Zhang, Yangfan Zhou*, Dehua Tang, Muhan Ni, Jinyu Zheng, Guifang Xu, Chunyan Peng, Shanshan Shen, Qiang Zhan, Xiaoyun Wang, Duanmin Hu, Wu-Jun Li#, Lei Wang#, Ying Lv#, and Xiaoping Zou#.

    eBioMedicine (Part of The Lancet Discovery Science),
    2022. [# denotes co-corresponding author]
    [pdf]

  • BASGD: Buffered Asynchronous SGD for Byzantine Learning.
    Yi-Rui Yang*, Wu-Jun Li.

    Proceedings of the International Conference on Machine Learning (ICML), 2021.
    [pdf][code]

  • Blocking-based Neighbor Sampling for Large-scale Graph Neural Networks.
    *, Wu-Jun Li.
    Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2021.
    [pdf][code]

  • CAM: Context-Aware Masking for Robust Speaker Verification.
    *, Siqi Zheng, Hongbin Suo, Yun Lei, Wu-Jun Li.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021.
    [pdf]

  • On the Convergence and Improvement of Stochastic Normalized Gradient Descent.
    Shen-Yi Zhao*, Yin-Peng Xie*, Wu-Jun Li.
    SCIENCE CHINA Information Sciences (SCIS), 2021.
    [pdf]

  • Densely Connected Time Delay Neural Network for Speaker Verification.
    *, Wu-Jun Li.
    Proceedings of the Annual Conference of the International Speech Communication Association (INTERSPEECH), 2020.
    [pdf]

  • DMNet: Difference Minimization Network for Semi-supervised Segmentation in Medical Images.
    *, Wu-Jun Li.
    Proceedings of the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020.
    [pdf]

  • ExchNet: A Unified Hashing Network for Accelerating Fine-Grained Image Retrieval.
    Quan Cui, Qing-Yuan Jiang*, Xiu-Shen Wei, Wu-Jun Li, Osamu Yoshie.
    Proceedings of the European Conference on Computer Vision (ECCV), 2020.
    [pdf]

  • Hashing based Answer Selection.
    *, Wu-Jun Li.
    Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020.
    [pdf]

  • SVD: A Large-Scale Short Video Dataset for Near Duplicate Video Retrieval.
    Qing-Yuan Jiang*, Yi He, Gen Li, Jian Lin*, Lei Li, Wu-Jun Li.
    Proceedings of International Conference on Computer Vision (ICCV), 2019.
    [pdf] [dataset]

  • Deep Hashing for Speaker Identification and Retrieval.
    Lei Fan*, Qing-Yuan Jiang*, Ya-Qi Yu*, Wu-Jun Li.
    Proceedings of the Annual Conference of the International Speech Communication Association (INTERSPEECH), 2019.
    [pdf]

  • Ensemble Additive Margin Softmax for Speaker Verification.
    Ya-Qi Yu*, Lei Fan*, Wu-Jun Li.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019.
    [pdf]

  • Discrete Latent Factor Model for Cross-Modal Hashing.
    Qing-Yuan Jiang*, Wu-Jun Li.
    IEEE Transactions on Image Processing (TIP), 2019.
    [pdf][MATLAB code]

  • Robust Frequent Directions with Application in Online Learning.
    Luo Luo, Cheng Chen, Zhihua Zhang, Wu-Jun Li, Tong Zhang.
    Journal of Machine Learning Research (JMLR),
    2019.
    [pdf]

  • Proximal SCOPE for Distributed Sparse Learning.
    Shen-Yi Zhao*, Gong-Duo Zhang*, Ming-Wei Li*, Wu-Jun Li.
    Advances in Neural Information Processing Systems (NeurIPS), 2018.
    [arXiv Version]

  • Deep Discrete Supervised Hashing.
    Qing-Yuan Jiang*, Xue Cui*, Wu-Jun Li.
    IEEE Transactions on Image Processing (TIP), 27(12): 5996-6009, 2018.
    [pdf] [code]

  • Asymmetric Deep Supervised Hashing.
    Qing-Yuan Jiang*, Wu-Jun Li.
    Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), 2018.
    [pdf] [PyTorch code] [MATLAB code]

  • Semi-Supervised Deep Hashing with a Bipartite Graph.
    Xinyu Yan, Lijun Zhang, Wu-Jun Li.
    Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2017.
    [pdf]
  • Deep Cross-Modal Hashing.
    Qing-Yuan Jiang*, Wu-Jun Li.
    Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
    2017.
    [pdf] [TensorFlow code] [MATLAB code]

  • SCOPE: Scalable Composite Optimization for Learning on Spark.
    Shen-Yi Zhao*, Ru Xiang*, Ying-Hao Shi*, Peng Gao*, Wu-Jun Li.
    Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017.
    [pdf]

  • Lock-Free Optimization for Non-Convex Problems.
    Shen-Yi Zhao*, Gong-Duo Zhang*, Wu-Jun Li.
    Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017.
    [pdf]

  • Feature Learning based Deep Supervised Hashing with Pairwise Labels.
    Wu-Jun Li, Sheng Wang*, Wang-Cheng Kang*.
    Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016.
    [pdf] [code]

  • Fast Asynchronous Parallel Stochastic Gradient Descent: A Lock-Free Approach with Convergence Guarantee.
    Shen-Yi Zhao*, Wu-Jun Li.
    Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), 2016.
    [pdf]

  • Column Sampling based Discrete Supervised Hashing.
    Wang-Cheng Kang*, Wu-Jun Li, Zhi-Hua Zhou
    Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), 2016.
    [pdf] [code]

  • Scalable Graph Hashing with Feature Transformation.
    Qing-Yuan Jiang*, Wu-Jun Li.
    Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI), 2015.
    [pdf] [code]

  • Learning to hash for big data: current status and future trends.
    Wu-Jun Li, Zhi-Hua Zhou.
    Chinese Science Bulletin, 60: 485-490, 2015. (In Chinese, Invited Paper) .
    [pdf]

  • Relational collaborative topic regression for recommender systems.
    Hao Wang*, Wu-Jun Li.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(5): 1343-1355, 2015.
    [pdf] [data]

  • Support Matrix Machines.
    Luo Luo, Yubo Xie, Zhihua Zhang, Wu-Jun Li.
    Proceedings of the 32nd International Conference on Machine Learning (ICML), 2015.
    [pdf] [code]

  • Multicategory large margin classification methods: hinge losses vs. coherence functions.
    Zhihua Zhang, Cheng Chen, Guang Dai, Wu-Jun Li, Dit-Yan Yeung.
    Artificial Intelligence, 215: 55-78, 2014.
    [pdf]

  • Distributed Power-law Graph Computing: Theoretical and Empirical Analysis.
    Cong Xie*, Ling Yan*, Wu-Jun Li, Zhihua Zhang.
    Proceedings of the 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014.
    [pdf] [longer version] [code]

  • Distributed Stochastic ADMM for Matrix Factorization.
    Zhi-Qin Yu*, Xing-Jian Shi*, Ling Yan*, Wu-Jun Li.
    Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM), 2014.
    [pdf]

  • Coupled Group Lasso for Web-Scale CTR Prediction in Display Advertising.
    Ling Yan*, Wu-Jun Li, Gui-Rong Xue, Dingyi Han.
    Proceedings of the 31st International Conference on Machine Learning (ICML), 2014.
    [pdf]

  • Supervised Hashing with Latent Factor Models.
    Peichao Zhang*, Wei Zhang*, Wu-Jun Li, Minyi Guo.
    Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2014.
    [pdf][MATLAB code]

  • Large-Scale Supervised Multimodal Hashing with Semantic Correlation Maximization.
    Dongqing Zhang*, Wu-Jun Li.
    Proceedings of theTwenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2014.
    [pdf][MATLAB code]

  • Online Egocentric models for citation networks.
    Hao Wang*, Wu-Jun Li.
    Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI),
    2013.
    [pdf]

  • Collaborative topic regression with social regularization for tag recommendation.
    Hao Wang*, Binyi Chen*, Wu-Jun Li.
    Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI),
    2013.
    [pdf] [data]

  • Isotropic hashing.
    Weihao Kong*, Wu-Jun Li.
    Proceedings of the 26th Annual Conference on Neural Information Processing Systems (NIPS),
    2012.
    [pdf] [MATLAB code]

  • Manhattan hashing for large-scale image retrieval.
    Weihao Kong*, Wu-Jun Li, Minyi Guo.
    Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR),
    2012.
    [pdf] [MATLAB code]

  • Double-bit quantization for hashing.
    Weihao Kong*, Wu-Jun Li.
    Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI),
    2012.
    [pdf] [MATLAB code]

  • Emoticon smoothed language models for Twitter sentiment analysis.
    Kun-Lin Liu*, Wu-Jun Li, Minyi Guo.
    Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI), 2012.
    [pdf]

  • Sparse probabilistic relational projection.
    Wu-Jun Li, Dit-Yan Yeung.
    Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI),
    2012.
    [pdf]

  • Social relations model for collaborative filtering.
    Wu-Jun Li, Dit-Yan Yeung.
    Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2011.
    [pdf]

  • Generalized latent factor models for social network analysis.
    Wu-Jun Li, Dit-Yan Yeung, Zhihua Zhang.
    Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI), 2011.
    [pdf][MATLAB code][Cora data]

  • MILD: Multiple-instance learning via disambiguation.
    Wu-Jun Li, Dit-Yan Yeung.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 22 (1): 76-89, 2010.
    [pdf] [MATLAB code and data]

  • Gaussian process latent random field.
    Guoqiang Zhong, Wu-Jun Li, Dit-Yan Yeung, Cheng-Lin Liu, Xinwen Hou.
    Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2010.
    [pdf]

  • Probabilistic relational PCA.
    Wu-Jun Li, Dit-Yan Yeung, Zhihua Zhang.
    Proceedings of the Twenty-Third Annual Conference on Neural Information Processing Systems (NIPS), 2009.
    [pdf] [MATLAB code] [longer version]

  • Relation regularized matrix factorization.
    Wu-Jun Li, Dit-Yan Yeung.
    Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI), 2009.
    [pdf] [slides] [MATLAB code] [data]

  • Localized content-based image retrieval through evidence region identification.
    Wu-Jun Li, Dit-Yan Yeung.
    Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2009.
    [pdf] [MATLAB code] [SIVAL data set] [COREL data set] [longer version]

  • TagiCoFi: Tag informed collaborative filtering.
    Yi Zhen, Wu-Jun Li, Dit-Yan Yeung.
    Proceedings of the Third ACM Conference on Recommender Systems (RecSys), 2009.
    [pdf] [code]

  • Latent Wishart processes for relational kernel learning.
    Wu-Jun Li, Zhihua Zhang, Dit-Yan Yeung.
    Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS), JMLR: W&CP 5, pp. 336-343, 2009.
    [pdf] [slides] [MATLAB code] [data]

  • Coherence functions for multicategory margin-based classification methods.
    Zhihua Zhang, Michael Jordan, Wu-Jun Li, Dit-Yan Yeung.
    Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS), JMLR: W&CP 5, pp. 647-654, 2009.
    [pdf]

  • Joint boosting feature selection for robust face recognition.
     
    Rong Xiao, Wu-Jun Li , Yuandong Tian, Xiaoou Tang.
    Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
    (CVPR) (2):1415-1422, 2006.
    [pdf]

PhD Thesis:
  • Latent Factor Models for Statistical Relational Learning. Department of Computer Science and Engineering, Hong Kong University of Science and Technology. 2010.
    [pdf]

Book (in Chinese):
Other Articles:
  • Research Skills Training for Undergraduate Students (In Chinese, 浅谈本科生科研能力培养).
    Wu-Jun Li.
    Invited by Communications of the China Computer Federation, 2013.
    [pdf]

Last updated: 02/2024