Xi-Zhu Wu @ LAMDA

Modified: 2014/08/25 22:19 by admin - Uncategorized
ImageChinese name
Xi-Zhu Wu (X.-Z. Wu)

PhD Candidate
LAMDA Group
Department of Computer Science
National Key Laboratory for Novel Software Technology
Nanjing University

email: wuxz # lamda.nju.edu.cn (I would reply within 24 hours, if not, please contact me using Gmail account "wuxz.gm")
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Currently I am a second year PhD student of Department of Computer Science and Technology in Nanjing University and a member of LAMDA Group(LAMDA Publications), led by professor Zhi-Hua Zhou.


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Supervisor

Professor Zhi-Hua Zhou.

Biography

I was admitted to study in Elite Project in September 2010 and received my B.Sc. degree in Computer Science in Kuangyaming Honor School of Nanjing University in June 2014. In the same year, I was admitted to study for a M.Sc. degree in Nanjing University without entrance examination. I am a PhD candidate since 2016.

Research Interest

I am interested in Machine Learning. Currently I am focusing on the subfields:
  • Multi-Label Learning : learning from objects with multiple labels;
  • Learnware : towards resuable, evolvable and comprehensible machine learning models.

Publication

  • Xi-Zhu Wu and Zhi-Hua Zhou. A Unified View of Multi-Label Performance Measures. In: Proceedings of the 34th International Conference on Machine Learning (ICML'17), Sydney, Australia, 2017. [PDF] [Supplementary PDF][code]

Awards & Honors

  • CCML Best Paper Award. 2017
  • The Second Prize in CCF Big Data Competition. 2014
  • Microsoft Youngfellow Scholarship. 2013
  • Excellent Project Completion in the Undergraduate Innovation Program. 2013
  • Elite Project Scholarship. 2013
  • Elite Project Scholarship. 2012

Teaching Assistant

  • Introduction to Machine Learning. Spring, 2017
  • Discrete Mathematics. Spring, 2017


Mail:
National Key Laboratory for Novel Software Technology, Nanjing University, Xianlin Campus Mailbox 603, 163 Xianlin Avenue, Qixia District, Nanjing 210023, China
(In Chinese:) 南京市栖霞区仙林大道163号,南京大学仙林校区603信箱,软件新技术国家重点实验室,210023。

Last modified: 2017-08-31