Yun Zhou PhD M.Eng B.Eng

Associate Professor

Science and Technology on Information Systems Engineering Laboratory
National University of Defense Technology
109 Deya Road
China 410072
E-mail: zhouyun AT nudt.edu.cn; zhouy.nudt AT gmail.com
ORCID: 0000-0001-7328-0275

I am a faculty in National University of Defense Technology since June 2016. I received my PhD degree from Risk Information Management Research Group in the School of Electronic Engineering and Computer Science at Queen Mary, University of London, jointly supervised by Prof. Norman Fenton, Prof. Timothy Hospedales and Prof. Martin Neil.

Before joining the RIM Group in QMUL I received my M.Eng and B.Eng in Information Systems from National University of Defense Technology supervised by Prof. Weiming Zhang and Prof. Cheng Zhu.


About Me

Research Interests

  • Robust Machine Learning (PI: Training Program for Excellent Young Innovators of Changsha KQ2009009, 12/2020-12/2025, ¥ 500,000)
  • Bayesian Network Learning (PI: NSFC Grant 61703416, 01/2018-12/2020, ¥ 210,000)
  • Transfer Learning (PI: HNSFC Grant 2018JJ3614, 06/2018-06/2020, ¥ 50,000)
  • Spatio-temporal Data Mining (PI: MoE Grant, 12/2016-12/2017, ¥ 20,000)

Education Background

  • June 2015 - 2016
    Postdoc in Tungsten Centre for Intelligent Data Analytics
    Goldsmiths, University of London, United Kingdom
  • Sept 2011 - 2015
    PhD in Computer Science supervised by Prof. Norman Fenton
    Queen Mary, University of London, United Kingdom
  • Sept 2009 - 2011
    M.Eng in Management Science and Engineering
    Supervised by Prof. Weiming Zhang
    National University of Defense Technology, China
  • Sept 2005 - 2009
    B.Eng in Information System Engineering (Hons)
    National University of Defense Technology, China

Professional Services

  • PC member of PGM-16
  • Invited Reviewer of IEEE Transactions on Neural Networks and Learning Systems
  • Invited Reviewer of IEEE Transactions on Industrial Informatics
  • Invited Reviewer of IEEE Transactions on Emerging Topics in Computational Intelligence
  • Invited Reviewer of Physica A: Statistical Mechanics and its Applications
  • Invited Reviewer of Knowledge-Based Systems
  • Invited Reviewer of International Journal of Approximate Reasoning
  • Invited Reviewer of IEEE Transactions on Knowledge and Data Engineering
  • Invited Reviewer of International Journal of Information Technology & Decision Making
  • Invited Reviewer of International Journal of Machine Learning and Cybernetics

My Erdos number is 4, with following:

  • Zhou, Y.; Howroyd, J. D; Danicic, S.; Bishop, M. Extending naive Bayes classifier with hierarchy feature level information for record linkage. Advanced Methodologies for Bayesian Networks LNCS. (2015), 9505, 93-104.
  • Falconer, K. J.; Howroyd, J. D. Projection theorems for box and packing dimensions. Math. Proc. Cambridge Philos. Soc. 119 (1996), no. 2, 287-295.
  • Croft, H. T.; Falconer, K. J. On maximal Euclidean sets avoiding certain distance configurations. Math. Proc. Cambridge Philos. Soc. 89 (1981), no. 1, 79-88.
  • Conway, J. H.; Croft, H. T.; Erdos, P.; Guy, M. J. T. On the distribution of values of angles determined by coplanar points. J. London Math. Soc. (2) 19 (1979), no. 1, 137-143.

Publication

My Google Scholar Profile

2021

  1. A New PC-PSO Algorithm for Bayesian Network Structure Learning with Structure Priors. Paper Code
    Baodan Sun, Yun Zhou, Jianjiang Wang, Weiming Zhang.
    Expert Systems with Applications, 2021.

  2. IDA-GAN: A Novel Imbalanced Data Augmentation GAN. Paper
    Hao Yang and Yun Zhou
    25th International Conference on Pattern Recognition (ICPR).

2020

  1. Random forest with self-paced bootstrap learning in lung cancer prognosis. Paper
    Qingyong Wang, Yun Zhou, Weiping Ding, Zhiguo Zhang, Khan Muhammad, Zehong Cao.
    ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 2020.

  2. Adaptive sampling using self-paced learning for imbalanced cancer data pre-diagnosis. Paper
    Qingyong Wang, Yun Zhou, Weiming Zhang, Zhangui Tang, Xiaojing Chen.
    Expert Systems with Applications, 2020.

  3. FSPMTL: Flexible Self-Paced Multi-Task Learning. Paper Code
    Lijian Sun and Yun Zhou.
    IEEE Access, 2020.

  4. MVDT-SI: A Multi-View Double-Triangle Algorithm for Star Identification. Paper
    Lijian Sun and Yun Zhou.
    Sensors, 2020.

  5. An unsupervised ensemble framework for node anomaly behavior detection in social network. Paper
    Cheng Qing, Yun Zhou, Yanghe Feng and Zhong Liu
    Soft Computing, 2020.

2019

  1. An ensemble learning approach for XSS attack detection with domain knowledge and threat intelligence. Paper
    Yun Zhou and Peichao Wang.
    Computers and Security, 2019.

  2. OA user behavior analysis with the heterogeneous information network model. Paper
    Lin Yang, Yilin Wang, Yun Zhou, Jiang Wang, Changjun Fan and Cheng Zhu
    Physica A: Statistical Mechanics and its Applications, 2019.

2018

  1. From Partition-based Clustering to Density-based Clustering: Fast Find Clusters with Diverse Shapes and Densities in Spatial Databases. Paper
    Jiang Wang, Cheng Zhu, Yun Zhou, Xianqiang Zhu, Yilin Wang and Weiming Zhang
    IEEE Access, 6:1718 - 1729, 2018.

  2. Interactive Temporal Recurrent Convolution Network for Traffic Prediction in Data Centers. Paper
    Xiaofeng Cao, Yuhua Zhong, Yun Zhou, Jiang Wang, Cheng Zhu and Weiming Zhang
    IEEE Access, 6:5276 - 5289, 2018.

  3. Dynamic Defense Strategy against Stealth Malware Propagation in Cyber-Physical Systems. Paper
    Kaiming Xiao, Cheng Zhu, Junjie Xie, Yun Zhou, Xianqiang Zhu and Weiming Zhang
    IEEE INFOCOM, Honolulu, USA, 2018.

2017

  1. A Framework for Key Element Evaluation of Combat System. Paper
    Peichao Wang, Yun Zhou, Jiang Wang, Cheng Zhu, Chao Chen and Weiming Zhang
    2017 IEEE International Conference on Systems, Man, and Cybernetics, Banff, Canada, 3101-3106, 2017.

  2. Multiple DAGs Learning with Non-negative Matrix Factorization. Paper Slides
    Yun Zhou, Jiang Wang, Cheng Zhu and Weiming Zhang
    The 3rd International Workshop on Advanced Methodologies for Bayesian Networks, PMLR 73:81-92, 2017.

  3. Shape-Based Analysis for Vessel Trajectories. Paper
    Jiang Wang, Yun Zhou, Xiaofeng Cao, Yilin Wang, Cheng Zhu and Weiming Zhang
    25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, California, 2017.

  4. Vessel Spatio-temporal Knowledge Discovery with AIS Trajectories Using Co-clustering. Paper
    Jiang Wang, Cheng Zhu, Yun Zhou and Weiming Zhang
    Journal of Navigation, 70(60): 1383-1400, 2017.

  5. Goal Recognition Assisted Decision Making in Security Games: A Real-time Attack Graph Interdiction Game. Paper
    Kaiming Xiao, Cheng Zhu, Kai Xu, Yun Zhou, Xianqiang Zhu and Weiming Zhang
    The 1st International Workshop on A.I. in Security (IWAISe 2017), IJCAI, Melbourne, 2017.

  6. Spectroscopic super-resolution fluorescence cell imaging using ultra-small Ge quantum dots. Paper
    Mingying Song, Ali Karatutlu, Isma Ali, Osman Ersoy, Yun Zhou, Yongxin Yang, Yuanpeng Zhang, William R. Little, Ann P. Wheeler and Andrei V. Sapelkin
    Optics Express, 25, 4240-4253, 2017.

  7. Improving Record Linkage Accuracy with Hierarchical Feature Level Information and Parsed Data. Paper
    Yun Zhou, Minlue Wang, Valeriia Haberland, John Howroyd, Sebastian Danicic and J. Mark Bishop
    New Generation Computing (NGC), 2017.

2016

  1. An Empirical Study of Bayesian Network Parameter Learning with Monotonic Influence Constraints. Paper Dataset
    Yun Zhou, Norman Fenton and Cheng Zhu.
    Decision Support Systems (DSS), 2016.

  2. When and Where to Transfer for Bayes Net Parameter Learning. Paper
    Yun Zhou, Timothy Hospedales and Norman Fenton
    Expert Systems with Applications (ESWA), 2016.

2015

  1. Extending Naive Bayes Classifier with Hierarchy Feature Level Information for Record Linkage. Paper Slides Dataset
    Yun Zhou, John Howroyd, Sebastian Danicic and J. Mark Bishop.
    Advanced Methodologies for Bayesian Networks (AMBN 2015), 2015.

  2. Probabilistic Graphical Models Parameter Learning with Transferred Prior and Constraints. Paper Slides Bibtex
    Yun Zhou, Norman Fenton, Timothy Hospedales and Martin Neil.
    31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), 2015.

2014

  1. An Extended MPL-C Model for Bayesian Network Parameter Learning with Exterior Constraints. Paper Manuscript
    Yun Zhou, Norman Fenton and Martin Neil.
    European Workshop on Probabilistic Graphical Models (PGM 2014), 2014.

  2. Bayesian Network Approach to Multinomial Parameter Learning using Data and Expert Judgements. Paper
    Yun Zhou, Norman Fenton and Martin Neil.
    International Journal of Approximate Reasoning (IJAR), 2014.

2013

  1. Incorporating Expert Judgement into Bayesian Network Machine Learning. Paper
    Yun Zhou, Norman Fenton, Martin Neil and Cheng Zhu.
    Proceedings of the 23th International Joint Conference on Artificial Intelligence (IJCAI 2013). 2013.

2011

  1. Parallel Algorithm of Electromagnetic Wave Propagation in Complex Terrain Environment. Zhou Yun, Zhu Cheng, Zhang Wei-ming, Huang Jin-cai and Liu Zhong.
    Computer Engineering 2011, 37(5) 261-263,266.

2010

  1. Modeling and simulation of dining process in restaurant based on Arena. Zhou Yun and Lu Xiao-jun.
    Highlights of Sciencepaper Online, 3(8), 2010, 750-755.

Research Group

PhD Students

  • Jiang Wang          Spatio-temporal Data Mining
  • Kaiming Xiao       Security Games
  • Xiaofeng Cao       Cyberspace Security Analysis

Master Students

  • Xueting Zhang      Multi-task Learning (Graduated, now at University of Edinburgh)
  • Yilin Wang             Anomaly Detection (Graduated, now at Ant Financial, Alibaba Group)
  • Peichao Wang      Risk Analysis of Web Attack Based on Domain Knowledge and Threat Intelligence (Graduated, now at Beijing)
  • Jingwen Yan        Behavior Analysis
  • Lijian Sun             Bayesian Network Learning

Supervised Final Year Projects

  • Wei Gu             Experiments on Text Topic Drift Analysis for Insider Detection (Distinction)
  • Pengbo Zhou      Student Performance Analysis with MOOC data (Pass)
  • Junxiao Zhou      CVE Mining and Analysis (Merit)

Talks and Presentations

  • Invited talk: "Bayesian Network Learning and its Applications in Insider Threat Analysis", Northwestern Polytechnical University, China. (24/09/2016)
  • The Second Workshop on Advanced Methodologies for Bayesian Networks 16-18 November 2015 Yokohama, Japan. (16/11/2015)
  • Oral presentation: "Probabilistic Graphical Models Parameter Learning with Transferred Prior and Constraints", 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), Amsterdam. (14/07/2015)
  • Azure Machine Learning for Research Workshop at Microsoft Research Cambridge, UK. (15/10/2014)
  • The 7th EuropeanWorkshop on Probabilistic Graphical Models, Utrecht, The Netherlands. (17/09/2014)
  • 2014 EECS Research Showcase, Queen Mary University of London, UK. (03/04/2014)
  • The 23rd International Joint Conference on Artificial Intelligence, Doctoral Consortium, Beijing, China. (05/08/2013)
  • The 5th PhD conference of EECS, Queen Mary University of London, London, UK. (02/07/2013)
  • BCS Doctoral Consortium, London, UK. (16/05/2013)
  • Forum for AI Research Students at AI-2012, Cambridge, UK. (10/12/2012)
  • "A Graphical Model - Bayesian network". R182-Presenting Your Research to an Audience. The Learning Institute, Queen Mary, University of London. (04/04/2012)
  • Technical public speaking for research students. Research Technique Module. Department of Electronic Engineering and Computer Science, Queen Mary, University of London. (15/02/2012)

Code

  • Yun Zhou, This code can convert the BN software - AgenaRisk network into the Matlab (Bayes Net Toolbox) format. Code
  • Baodan Sun, Yun Zhou, Bayesian Network Structure Learning with Improved Genetic Algorithm (Submitted to International Journal of Intelligent Systems) Code

Group Pics

  • Group visit to Baidu company（Dec. 2017）
  • Shared Bike Tour in Shenzhen city（Dec. 2017）