Wenjun Hu

· Personal Information

副研究员(自然科学)

Supervisor of Doctorate Candidates

Supervisor of Master's Candidates

Gender:Male

Status:Employed

Teacher College:School of Life Science and Technology

Department:School of Life Science and Technology

Education Level:Postgraduate (Doctoral)

Degree:Doctoral Degree in Medicine

Alma Mater:京都大学

Discipline: Biochemistry and Molecular Biology
Biomedical Engineering
Oncology

Honors and Titles:
2021    武汉英才优秀青年人才

· Other Contact Information:

ZipCode:

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· Personal Profile

Now I am an Associated Professor of College of Life Science and Technology at the Huazhong University of Science and Technology. My research interest is focused on the applications of nanophotonics for bioanalytical and biomedical devices using plasmonic/dielectric metasurfaces, microfluidics, nanofabrication, and data analysis. Nanophotonics excels at confining light into nanoscale optical mod...

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· Education Experience

2011.4 ~ 2015.7
 京都大学   Doctoral Degree in Medicine  -  Postgraduate (Doctoral) 
2006.9 ~ 2009.6
 华中科技大学   Professional Master's Degree in Clinical Medicine  -  Postgraduate (Master's Degree) 
2001.9 ~ 2006.6
 华中科技大学   Undergraduate (Bachelor’s degree) 

· Work Experience

No content

· Social Affiliations

2022.4-2022.4
《Biosensor》Guest Editor
2021.11-2022.4
《Journal of Gene Medicine》
2022.1-2022.4
《解放军医学杂志》青年编委

Welcome to my home page!

· Research Group

· Name of Research Group:Department of Nano B

Description of Research Group:Mainly focusing on the surface-based equipartitioned excitation biosensing chip and its application in the field of bio-imaging and molecular detection and other aspects of related research work and talent training, cohesion of a team of talents from biomedical engineering, immunohistology, pharmacy, electronics and other disciplines, and gradually build the SPR technological innovation platform to cultivate outstanding scientific and technological innovation talents.

Main research areas:
a. Ultra-sensitive micro-nano novel biosensors;
b. Large-scale label-free biological single-molecule detection technology;
c. Wide application of mobile sensing technology in medicine, biology, etc.;
d. Deep-learning cloud computing biosensing data and artificial intelligence diagnostic system.