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地址: 南山区西丽大学城清华园区信息大楼1609

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  • 个人简历
  • 教学
  • 研究领域
  • 研究成果
  • 奖励荣誉
  • 概况

    教育经历

    1992年9月-1997年1月,南开大学,数学系,信息论编码专业,博士

    1988年9月-1992年7月,南开大学,数学系,数学专业,学士


    工作经历

    2019年8月-至今,清华大学深圳国际研究生院,教授、博士生导师

    2007年12月-2019年8月,清华大学深圳研究生院,教授、博士生导师(2009年)

    2004年1月-2007年12月,清华大学深圳研究生院,副研究员

    1997年9月-1998年9月,香港中文大学信息工程系,访问学者


    学术兼职

    中国电子学会高级会员

    中国电子学会信息论分会委员


    社会兼职

  • 教学课程

    研究生课程:信道编码、应用信息论基础

    研究生指导

  • 研究领域

    主要从事信息论编码、互联网与人工智能等方向的教学与科研工作,目前的主要研究兴趣为编码/量化/压缩、AI互联网及机器学习算法等。在IEEE Transactions on Information Theory (TIT), TSP, TNNLS, TCOM, ToN等国际权威期刊和NIPS, ICML, ICLR, CVPR, ICCV, ECCV, MM, AAAI, IJCAI等领域顶级会议上发表论文一百多篇。近年来完成多项国家级科研项目,其中主持的项目有:

    1.复杂动态互联网行为的基准建模与异常分析,国家重点研发计划重点专项,课题负责人,2019.7-2022.6, 176.

    2.未来互联网的高效路由与智能传输机理,国家973课题,2012.1-2016.12527.

    3.基于校验矩阵方法的局部修复码研究与应用,国家自然科学基金,2018.1-2021.1267.

    4.基于LDPC码的压缩感知测量矩阵构造及性能分析,国家自然科学基金,2014.1-2017.1282.

    5.Non-coherent网络中的纠错码及其应用,国家自然科学基金,2010.1-2012.1230.

    6.LDPC码的译码性能分析及应用,国家自然基金委与广东省政府联合基金,2007.1-2009.1230.

    7.二元码的检错/纠错性能估计和应用,国家自然科学基金,2005.1-2007.1223.

    8.面向未来网络的内容分发技术研究,深圳市科创委技术攻关项目,2015.7-2017.12400.

    9.深圳智能语义挖掘技术工程实验室,深圳市发改委,2012.11- 2014.12500.

    10.大规模机器学习算法的噪声鲁棒性及在证券交易领域的应用研究,深圳市基础研究学科布局项目,2019.1-2021.12,300万.


    主要项目

  • 代表性论文

    机器学习、稀疏表示及应用

    [1]       Dongxian Wu, Yisen Wang, Shu-Tao Xia. Adversarial Weight Perturbation Improves Adversarial Training, Proc. Neural Information Processing Systems (NIPS-20), accepted, Virtual Conference, Dec. 2020.

    [2]       Naiqi Li, Wenjie Li, Jifeng Sun, Yinghua Gao, Yong Jiang, Shu-Tao Xia. Stochastic Deep Gaussian Processes over Graphs, Proc. Neural Information Processing Systems (NIPS-20), accepted, Virtual Conference, Dec. 2020.

    [3]       Tao Dai, Yan Feng, Dongxian Wu, Bin Chen, Jian Lu, Yong Jiang, Shutao Xia. DIPDefend: deep image prior driven defense against adversarial examples, Proc. the 28th ACM International Conference on Multimedia (MM-20), Virtual Conference, Seattle, U.S.A., Oct. 2020.

    [4]       Jiawang Bai, Bin Chen, Yiming Li, Dongxian Wu, Weiwei Guo, Shu-Tao Xia, En-Hui Yang. Targeted attack for deep hashing based retrieval, Proc. the 16th European Conference on Computer Vision (ECCV-20), oral paper, Virtual Conference, Aug. 2020.

    [5]       Yang Bai, Yuyuan Zeng, Yong Jiang, Yisen Wang, Shu-Tao Xia, Weiwei Guo. Improving query efficiency of black-box adversarial attack, Proc. the 16th European Conference on Computer Vision (ECCV-20), Virtual Conference, Aug. 2020.

    [6]       Haoyu Liang, Zhihao Ouyang, Yuyuan Zeng, Hang Su, Zihao He, Shu-Tao Xia, Jun Zhu, Bo Zhang. Training interpretable convolutional neural networks by differentiating class-specific filters, Proc. the 16th European Conference on Computer Vision (ECCV-20), oral paper, Virtual Conference, Aug. 2020.

    [7]       Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma, Skip connections matter: on the transferability of adversarial examples generated with RESNETs, Proc. International Conference on Learning Representations (ICLR-20), spotlight paper, Virtual Conference, Addis Ababa, Ethiopia, Apr. 2020.

    [8]       Bowen Zhao, Xi Xiao, Guojun Gan, Bin Zhang, Shutao Xia, Maintaining discrimination and fairness in class incremental learning, Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR-20), Seattle, Washington, U.S.A., Jun. 2020.

    [9]       Xuesong Chen, Xiyu Yan, Feng Zheng, Yong Jiang, Shu-Tao Xia, Yong Zhao, Rongrong Ji, One-shot adversarial attacks on visual tracking with dual attention, Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR-20), Seattle, Washington, U.S.A., Jun. 2020.

    [10]    Yan Feng, Bin Chen, Tao Dai, Shu-Tao Xia, Adversarial attack on deep product quantization network for image retrieval, Proc. the 34st AAAI Conference on Artificial Intelligence (AAAI-20), New York, USA, Feb. 2020.

    [11]    Jiacheng Yang, Bin Chen, Shu-Tao Xia, Mean-removed product quantization for large-scale image retrieval, Neurocomputing, vol.406, pp. 77-88, Sep. 2020.

    [12]    Xi Xiao, Dianyan Zhang, Guangwu Hu, Yong Jiang, Shutao Xia, CNNMHSA: a convolutional neural network and multi-head self-attention combined approach for detecting phishing websites, Neural Networks (NN),vol. 125, pp. 303312, 2020.

    [13]    Zhendong Peng, Xi Xiao, Guangwu Hu, Arun Kumar Sangaiah, Mohammed Atiquzzaman, Shutao Xia. ABFL: an autoencoder based practical approach for software fault localization, Information Sciences (IS), vol. 510, pp. 108-121, Feb. 2020.

    [14]    Tao Dai, Jianrui Cai, Yongbing Zhang, Shu-Tao Xia, Lei Zhang. Second-order attention network for single image super-resolution, Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR-19), oral paper, Long Beach, CA, U.S.A., Jun. 2019.

    [15]    Yang Bai, Yan Feng, Yisen Wang, Tao Dai, Shu-Tao Xia, Yong Jiang. Hilbert-based generative defense for adversarial examples, Proc. International Conference on Computer Vision (ICCV-19), pp. 4784-4793, Seoul, Korea, Oct.-Nov. 2019.

    [16]    Hongshan Li, Yu Guo, Zhi Wang, Shutao Xia, Wenwu Zhu. AdaCompress: adaptive compression for online computer vision services, Proc. the 27th ACM International Conference on Multimedia (MM-19), pp. 2440-2448, Nice, France, Oct. 2019.

    [17]    Xiyu Yan, Shuai Chen, Zihao He, Chunmei Li, Feng Zheng, Tao Dai, Shuo Dong, Yong Jiang, Shu-Tao Xia. Automatic grassland degradation estimation using deep learning, Proc. the 28th International Joint Conference on Artificial Intelligence (IJCAI-19), Macao, China, Aug. 2019.

    [18]    Xi Xiao, Rui Li, Hai-Tao Zheng, Runguo Ye, Arun KumarSangaiah, Shutao Xia, Novel dynamic multiple classification system for network traffic, Information Sciences (IS), vol. 479, pp. 526-541, 2019.

    [19]    Jin-Yuan Chen, Hai-Tao Zheng, Yong Jiang, Shu-Tao Xia, Cong-Zhi Zhao. A probabilistic model for semantic advertising, Knowledge and Information Systems (KIS), vol. 59, pp. 387-412, May 2019.

    [20]    Weizhi Lu, Weiyu Li, Wei Zhang, and Shu-Tao Xia. Expander recovery performance of bipartite graphs with girth greater than 4, IEEE Transactions on Signal and Information Processing over Networks, pp. 418-427, vol. 5, no. 3, Sep. 2019.

    [21]    Songtao Wang, Dan Li, Yang Cheng, Jinkun Geng, Yanshu Wang, Shu-Tao Xia and Jianping Wu. BML: a high-performance, low-cost gradient synchronization algorithm for DML training, Proc. Neural Information Processing Systems (NIPS-18), Montreal, Canada, Dec. 2018.

    [22]    Xingjun Ma, Yisen Wang, Michael E. Houle, Shu-Tao Xia, James Bailey. Dimensionality-driven learning with noisy labels, Proc. the Thirty-fifth International Conference on Machine Learning (ICML-18), long talk, Stockholm, Sweden, Jul. 2018.

    [23]    Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, and Shu-Tao Xia. Iterative learning with open-set noisy labels, Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR-18), spotlight paper, Salt Lake City, U.S.A., Jun. 2018.

    [24]    Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, Xingquan Zhu. A novel consistent random forests framework: Bernoulli random forests. IEEE Transactions on Neural Networks and Learning Systems(TNNLS), vol. 29, no. 8, pp. 3510-3523, Aug. 2018.

    [25]    Rui Li, Xi Xiao, Shiguang Ni, Haitao Zheng, Shutao Xia, Byte segment neural network for network traffic classification, Proc. IEEE/ACM International Symposium on Quality of Service (IWQoS-18), Banff, Alberta, Canada, Jun. 2018.

    [26]    Weizhi Lu, Tao Dai, Shu-Tao Xia. Binary matrices for Compressed Sensing, IEEE Transactions on Signal Processing (TSP), vol. 66, no. 1, pp. 77-85, Jan. 2018.

    [27]    Chaobing Song, Shaobo Cui, Yong Jiang, Shu-Tao Xia. Accelerated stochastic greedy coordinate descent by soft thresholding projection onto simplex. Proc. Neural Information Processing Systems (NIPS-17), spotlight paper, Long Beach, U.S.A., Dec. 2017.

    [28]    Qingtao Tang, Tao Dai, Li Niu, Yisen Wang, Shu-Tao Xia, and Jianfei Cai. Robust Survey Aggregation with Student-t Distribution and Sparse Representation. Proc. the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), pp. 2829-2835, Melbourne, Australia, Aug. 2017.

    [29]    Qingtao Tang, Li Niu, Yisen Wang, Tao Dai, Wangpeng An, Jianfei Cai, Shu-Tao Xia. Student-t Process Regression with Student-t Likelihood. Proc. the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), pp. 2822-2828, Melbourne, Australia, Aug. 2017.

    [30]    Xin-Ji Liu, Shu-Tao Xia, and Fang-Wei Fu, Reconstruction guarantee analysis of basis pursuit for binary measurement matrices in compressed sensing, IEEE Transactions on Information Theory (TIT), vol. 63, no. 5, pp. 2922-2932, May 2017.

    [31]    Y. Wang, S. Romano, N.X. Vinh, J. Bailey, X. Ma, S.-T. Xia. Unbiased multivariate correlation analysis, Proc. the 31st AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, California, U.S.A., Feb. 2017.

    [32]    Yisen Wang, Fangbing Liu, Shu-Tao Xia, Jia Wu. Link sign prediction by variational Bayesian probabilistic matrix factorization with student-t prior, Information Sciences (IS), vol. 405, pp. 175-189, 2017.

    [33]    Yisen Wang, Shu-Tao Xia, and Jia Wu, A less-greedy two-term Tsallis Entropy Information Metric approach for decision tree classification, Knowledge-Based Systems (KBS), vol. 120, pp. 34-42, Mar. 2017.

    [34]    Weizhi Lu, Tao Dai, and Shu-Tao Xia, Compressed Sensing Performance of Binary Matrices with Binary Column Correlations, Proc. 2017 Data Compression Conference (DCC-17), pp. 151-160, Snowbird, Utah, U.S.A., Apr. 2017.

    [35]    Yisen Wang, Qingtao Tang, Shu-Tao Xia, Jia Wu, Xingquan Zhu, Bernoulli random forests: closing the gap between theoretical consistency and empirical soundness, Proc. the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), pp. 2167-2173, New York, U.S.A., Jul. 2016.

    [36]    Tao Dai, Ke Gu, Li Niu, Yong-bing Zhang, Weizhi Lu, Shu-Tao Xia. Referenceless quality metric of multiply-distorted images based on structural degradation. Neurocomputing, vol. 290, pp. 185-195, May 2018.

    [37]    Tao Dai, Weizhi Lu, Wei Wang, Jilei Wang, and Shu-Tao Xia, Entropy-based bilateral filtering with a new range kernel, Signal Processing, vol. 137, pp. 223-234, Aug. 2017.

    [38]    S.-T. Xia, X.-J. Liu, Y. Jiang, and H.-T. Zheng, Deterministic constructions of binary measurement matrices from finite geometry, IEEE Transactions on Signal Processing (TSP), vol. 63, no. 4, pp. 1017-1029, Feb. 2015.

    [39]    F. Zhou, S.-T. Xia, and Q. Liao. Nonlocal pixel selection for multisurface fitting-based super-resolution. IEEE Transactions on Circuits and systems for video technology (TCSVT), vol. 24, no.12, pp. 2013-2017, Dec. 2014.

     

    信息论编码及网络

    [40]    Bin Chen, Weijun Fang, Shu-Tao Xia, Jie Hao, Fang-Wei Fu. Improved bounds and singleton-optimal constructions of locally repairable codes with minimum distance 5 and 6, IEEE Transactions on Information Theory (TIT), accepted, Oct. 2020.

    [41]    Jie Hao, Shu-Tao Xia, Kenneth W. Shum, Bin Chen, Fang-Wei Fu, Yixian Yang. Bounds and constructions of locally repairable codes: parity-check matrix approach, IEEE Transactions on Information Theory (TIT), accepted, Aug. 2020.

    [42]    Songtao Wang, Dan Li, Yang Cheng, Jinkun Geng, Yanshu Wang, Shuai Wang, Shutao Xia, and Jianping Wu. A scalable, high-performance, and fault-tolerant network architecture for distributed machine learning, IEEE Transactions on Networking (ToN), vol.28, no.4, pp. 1752-1764, Aug. 2020.

    [43]    Bin Chen, Weijun Fang, Shu-Tao Xia, and Fang-Wei Fu. Constructions of optimal (r,δ) locally repairable codes via constacyclic Codes, IEEE Transactions on Communications (TCOM) , pp. 5253-5263, vol. 67, no. 8, Aug. 2019.

    [44]    Bin Chen, Shu-Tao Xia, Jie Hao, and Fang-Wei Fu. Constructions of optimal cyclic (r,δ) locally repairable codes, IEEE Transactions on Information Theory (TIT), vol. 64, no. 4, pp. 2499-2511, Apr. 2018.

    [45]    Xi Xiao, Peng Fu, Changsheng Dou, Qing Li, Guangwu Hu, and Shutao Xia. Design and analysis of SEIQR worm propagation model in mobile internet, Communications in Nonlinear Science and Numerical Simulation, vol. 43, pp. 341-350, Feb. 2017.

    [46]    Qing Li, Mingwei Xu, Qi Li, Dan Wang, Yong Jiang, Shu-Tao Xia, Qingmin Liao. Scale the Internet routing table by generalized next hops of strict partial order, Information Sciences (IS), vol. 412, pp. 101-115, Oct. 2017.

    [47]    Yong Cui, Lian Wang, Xin Wang, Yisen Wang, Fengyuan Ren, Shutao Xia. End-to-end coding for TCP, IEEE Network, vol. 30, no. 2, pp. 68-73, Mar. 2016.

    [48]    Y. Jiang, S.-T. Xia, and F.-W. Fu. Stopping set distributions of some kinds of Reed-Muller codes, IEEE Transactions on Information Theory (TIT), vol. 57, no. 9, pp. 6078-6088, Sep. 2011.

    [49]    S.-T. Xia and F.-W. Fu, Minimum pseudo-weight and minimum pseudo-codewords of LDPC Codes, IEEE Transactions on Information Theory (TIT), vol. 54, no. 1, pp. 480-485, Jan. 2008.

    [50]    S.-T. Xia, F.-W. Fu, and S. Ling, A lower bound on the probability of undetected error for binary constant weight codes. IEEE Transactions on Information Theory (TIT), vol. 52, no. 9, pp. 4235-4243, Sep. 2006.

    [51]    S.-T. Xia, F.-W. Fu, Y. Jiang, and S. Ling, The probability of undetected error for binary constant weight codes. IEEE Transactions on Information Theory (TIT), vol. 51, no. 9, pp. 3364-3373, Sep. 2005.

    [52]    F.-W. Fu, T. Klove, and S.-T. Xia, The undetected error probability threshold of m-out-of-n codes, IEEE Transactions on Information Theory (TIT), vol.46, no.4, pp.1597-1599, Jul. 2000.

    [53]    F.-W. Fu and S.-T. Xia, Binary constant weight codes for error detection, IEEE Transactions on Information Theory (TIT), vol. 44, no. 3, pp. 1294-1299, May 1998.

    [54]    S.-T. Xia and F.-W. Fu, Johnson type bounds on constant dimension codes. Designs, Codes and Cryptography,vol.50, no.2, pp. 163-172, 2009.

    [55]    S.-T. Xia and F.-W. Fu, Undetected error probability of q-ary constant weight codes. Designs, Codes and Cryptography,vol. 48, pp. 125-140, 2008.

    [56]    F.-W. Fu and S.-T. Xia, The characterization of binary constant weight codes meeting the bound of Fu and Shen, Designs, Codes and Cryptography, vol.43, pp. 9-20, 2007.

    [57]    S.-T. Xia, F.-W. Fu, and Y. Jiang, On the minimum average distance of binary constant weight codes, Discrete Mathematics, vol. 308, pp. 3847-3859, 2008.

    [58]    S.-T. Xia and F.-W. Fu, On the average Hamming distance for binary codes. Discrete Applied Mathematics, vol. 89, pp. 269-276, 1998.

    [59]    Weijun Fang, Bin Chen, Shu-Tao Xia, Fang-Wei Fu, Complete characterization of optimal lrcs with minimum distance 6 and locality 2: improved bounds and constructions, ISIT-20, pp. 595-599, Los Angeles, USA, Jun. 2020.

    [60]    Jie Hao, Jun Zhang, Shu-Tao Xia, Fang-Wei Fu, Yi-Xian Yang, Weight distributions of q-ary optimal locally repairable codes with locality 2, distance 5 and even dimension, ISIT-20, pp. 611-615, Los Angeles, USA, Jun. 2020.

    [61]    Weijun Fang, Bin Chen, Shu-Tao Xia, Fang-Wei Fu, Perfect LRCs and k-optimal LRCs, ISIT-20, pp. 600-604, Los Angeles, USA, Jun. 2020.

    [62]    Xiaoteng Ma, Qing Li, Jimeng Chai, Xi Xiao, Shu-tao Xia, Yong Jiang. Steward: smart edge based joint QoE optimization for adaptive video streaming. Proc. the 29th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV-19), pp. 31-36, Amherst, MA, USA, Jun. 2019.

    [63]    Jie Hao, Kenneth W. Shum, Shu-Tao Xia, Yi-Xian Yang. Classification of optimal ternary (r,\delta)-locally repairable codes attaining the Singleton-like bound, Proc. IEEE International Symposium on Information Theory (ISIT-19), pp. 2828-2832, Vail, Paris, France, Jul. 2019.

    [64]    Bin Chen, Shu-Tao Xia, Jie Hao. Improved bounds and optimal constructions of locally repairable codes with distance 5 and 6, Proc. IEEE International Symposium on Information Theory (ISIT-19), pp. 2823-2827, Vail, Paris, France, Jul. 2019.

    [65]    Bin Chen, Shu-Tao Xia, Jie Hao, and Fang-Wei Fu, On optimal pseudo-cyclic (r,δ)  locally repairable codes, Proc. IEEE International Symposium on Information Theory (ISIT-18), pp. 1191-1195, Vail, Colorado, USA, Jun. 2018.

    [66]    Jie Hao, Kenneth W. Shum, Shu-Tao Xia, and Yixian Yang, On the maximal code length of optimal linear locally repairable codes, Proc. IEEE International Symposium on Information Theory (ISIT-18), pp. 1326-1330, Vail, Colorado, USA, Jun. 2018.

    [67]    Jie Hao, Shu-Tao Xia, and Bin Chen, On optimal ternary locally repairable codes, Proc. IEEE International Symposium on Information Theory (ISIT-17), pp. 171-175, Aachen, Germany, Jun. 2017.

    [68]    Bin Chen, Shu-Tao Xia, and Jie Hao, Locally repairable codes with multiple (ri, δi)-localities, Proc. IEEE International Symposium on Information Theory (ISIT-17), pp. 2038-2042, Aachen, Germany, Jun. 2017.

    [69]    J. Hao, S.-T. Xia, and B. Chen, Some results on optimal locally repairable codes, Proc. IEEE International Symposium on Information Theory (ISIT-16), pp. 440-444, Barcelona, Spain, Jul. 2016.

    [70]    J. Hao, S.-T. Xia, and B. Chen, Recursive bounds for locally repairable codes with multiple repair groups, Proc. IEEE International Symposium on Information Theory (ISIT-16), pp. 645-649, Barcelona, Spain, Jul. 2016.


    代表性著作

    主要专利成果

    其他成果

  • 荣誉奖项