基本信息
浏览量:135
职业迁徙
个人简介
Research interests: Deep Learning, Computer Vision, Bioinformatics
During my PhD I proposed simplified solutions for a few important scientific problems. These include:
How to train artificial neural networks better?
Network Deconvolution
Innovated redundancy reduction in feature pixels and channels to improve the convergence of training deep neural networks.
Show a possible relation with Hubel and Wiesel's center-surround structures and sparse representations.
How to assemble genomes more efficiently?
From Long Erroneous Sequencing Data
Reduce the redundancy in the third generation sequencing data (project name: DBG2OLC). The work reduced the human genome assembly time from 405,000 CPU hours to <2000 CPU hours (or ~ 200X speedup)
The approach has been used to assemble hundreds of genomes, including apple, lamprey, fruit fly, bat.
From Short Sequencing Data
Reduce the redundancy in the de Bruijn graph representation to achieve memory-efficient genome assembly algorithm for the second-generation sequencing.
The work (project name: SparseAssembler) has reduced the computational memory requirement of this fundamental task by 90%.
This work has been adopted by BGI-Shenzhen to assemble thousands of genomes.
研究兴趣
论文共 34 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
Jing Luo,Jing Chai, Yanling Wen,Min Tao,Guoliang Lin,Xiaochuan Liu,Li Ren, Zeyu Chen,Shigang Wu,Shengnan Li,Yude Wang,Qinbo Qin,
Science advancesno. 22 (2020): eaaz7677-eaaz7677
Chengxi Ye,Matthew Evanusa,Hua He, Anton Mitrokhin, Thomas Goldstein,James A. Yorke,Cornelia Fermüller,Yiannis Aloimonos
CoRR (2019)
引用18浏览0EI引用
18
0
Nature geneticsno. 2 (2018): 270-277
2018 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) (2018): 4640-4647
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn