Team:Beijing Normal/Team

From 2008.igem.org

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Image:Forrest.JPG| Forrest Sheng Bao
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Image:Forrest.JPG| [[User:Forrest_Bao|Forrest Sheng Bao]]
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Image:Team_member_3.png|Team member 3
Image:Team_member_3.png|Team member 3

Revision as of 04:55, 21 July 2008

thum Home The Team The Project Parts Submitted to the Registry Modeling Notebook


Who are we?


Advisors:

  • Advisor 1: Junfeng Niu
  • Advisor 2: Shi Chen

Students:

  • Student 1: Gang Wu
  • Student 2: Jingyi Wang
  • Student 3: Ya He
  • Student 4: Sheng Feng
  • Student 5: Forrest Sheng Bao

Where are we from?

Forrest Sheng Bao is from Dept. of Computer Science and Dept. of Electrical Engineering, Texas Tech University, Texas, USA. He is a master student in Electrical Engineering and PhD student in Computer Science. He obtained a bachelor degree in electrical engineering in 2006. This is his iGem page.


What have we done?

Forrest Sheng Bao's research interests are in artificial intelligence, biomedical engineering and bioinformatics. He is very interested on algorithms in biology and medicine fields, as well as the interdisciplinary fields of computing and biology.

This is his publications:(Full version CV)

  • Sheng Bao, et al., A DNA Sequence Compression Algorithm Based on LUT and LZ77, Proc. of IEEE ISSPIT 2005, p.23-28, 2005 pdf
  • Sheng Bao, et al., A Novel Sorting Algorithm Based on Guessing Function, Proc. of IEEE ISSPIT 2006, p.411 - 414, 2006 (pdf)
  • Yijin Zhang, Forrest Sheng Bao, et al., Analysis of Energy Efficiency and Power Saving in IEEE 802.15.4, IEEE WCNC 2007, 2007
  • Yu-Xuan Wang and Forrest Sheng Bao, An Entropy-based Weighted Clustering Algorithm and Its Optimization for Ad hoc Networks, IEEE WiMob 2007, 2007 (pdf)
  • Stephen Gang Wu, Forrest Sheng Bao, Eric You Xu, Yu-Xuan Wang, Yi-Fan Chang and Chiao-Liang Shiang, A Leaf Recognition Algorithm for Plant classification Using Probabilistic Neural Network, IEEE ISSPIT 2007, 2007 pdf
  • Zhendong Zhao, Lei Yuan, Yuxuan Wang, Forrest Sheng Bao,A Novel Model of Working Set Selection for SMO Decomposition Methods, IEEE ICTAI 2007, 2007 (pdf)