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Laboratory of Cognitive Computation and Applied Technology (LCCAT) stands for a research group led by Prof. Kaizhu Huang, based in Department of Electrical and Electronics Engineering of the Xi'an Jiaotong Liverpool University (XJTLU), Suzhou, China. The main research interests of LCCAT are in Pattern Recognition, Machine Learning, and their applications in text, image, sound, and video. Research in PremiLab has been supported by many grants such as National Basic Research Foundation, NSFC, and RDF@XJTLU, and some national and international research units.  LCCAT has published 8 books in Springer and about 200 papers. In particular, LCCAT members have published high-quality papers in top conferences papers (e.g., NIPS, ICDM, IJCAI, UAI, ICML, CVPR, SIGIR, ECML, WSDM) and top journals (e.g., IEEE T-PAMI, IEEE-T-NNLS, IEEE-T Cybernetics, IEEE-T IP, JMLR, Neural Computation, Machine Learning).

Recent Highlight

  • Potential PhD students or Postdoc are welcome to contact Prof. Huang (Email: A@B, A=kaizhu.huang, B=xjtlu.edu.cn). We offer full scholarship for PhD students and competitive salary to Postdocs. The projects will be mainly on deep learning and artificial intelligence.
  • We are organizing a special issue on Collaborative Computing for Data-Driven Systems on ACM Springer Mobile Networks and Applications (MONET) Journal. Submission Deadline: Feb 28, 2019. Submission can be made on https://www.springer.com/engineering/signals/journal/11036
  • We are organizing a special issue on Big Data Analytics for Secure and Smart Environmental Services in Remote Sensing (ISI Impact Factor 3.406). Submission Deadline: 30 June 2019. Submission can be made on https://www.mdpi.com/journal/remotesensing/special_issues/big_rs


  • We have actively published in top AI conferences in 2020 including 2 AAAI, 1 ACM MM, 1 ECCV, and 1 ECML papers! Congratulations to all the members for these excellent achievements!.
  • Prof. Kaizhu Huang presents a tutorial in adversarial learning in IEEE SMC 2019, held in Bari, Italy, 6-9 Oct., 2019.
  • Prof. Kaizhu Huang is invited as the keynote speaker in 9th International Conference on Brain Inspired Cognitive Systems (BICS 2018) (http://bics2018.org), held in Xi'an,China, 7-8 July, 2018.
  • In May, 2018, Prof. Kaizhu Huang is invited to join the Program Committee in the top conference Neural Information Processing Systems (NIPS) 2018.
  • Jan. 2018 two papers about field classification Bayesian matrix factorization were accepted by IEEE Trans. On Emerging Topics in Computational Intelligence. Congratulations to Haochuan and Xi.
  • August 2017 two papers about kernel methods and zeroshot classification were accepted by IEEE Trans. Circuit and Systems, and IEEE Trans. Image Processing respectively.
  • December 2016 New book proposal Deep Learning: Fundamentals, Theory, and Applications was accepted by Springer. The new book is expected to appear in 2018.
  • December 2016 Kaizhu Huang was invited to present a keynote speech entitled "Statistical Collective Classification: Theory and Applications" in IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016).
  • December 2016 Kaizhu Huang was invited as PC member in the world-leading AI conference 2017 International Joint Conference on Artificial Intelligence (IJCAI 2017).
  • July 8 2016 two papers were accepted by International Conference on Neural Information Processing (ICONIP2016).
  • June 2016 One paper was accepted by 15th IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2016) held in Stanford Univ., with the acceptance rate less than 30%
  • April 2016 Kaizhu Huang was invited as Senior PC member (Area Chair) in the top AI conference AAAI-2017
  • April 5th, 2016 Kaizhu Huang was invited to join (as the associate editor role) the editorial board of prestigious journal Cognitive Computation (JCR Tier 1 Journal).
  • Dec 22th, 2015 One paper was accepted by a Springer journal International Journal of Machine Learning and Computing . Congratulations to Haochuan!
  • Dec 18th, 2015 Kaizhu Huang was invited to give a talk titled Learning similarity from data: a sparse and robust perspective at Tsinghua University.
  • Dec 16th, 2015 Kaizhu Huang was invited to give a talk titled A unified gradient regularization family for adversarial examples at University of Electrical Science and Technology of China

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