其他成员(姓氏笔画为序)
周骏 教授
发布时间: 2025-05-30 11:47 作者:本站编辑 来源: 本站原创 浏览次数:

计算机与信息科学学院教授、博士、硕导

邮箱:zhouj@swu.edu.cn

教育经历

电子科技大学工学博士(2008-2013

研究及工作经历

美国罗切斯特大学(University of Rochester)博士后(2014-2015

毕业后在西南大学计算机与信息科学学院工作至今

研究方向

机器学习,图像处理,计算机视觉,智能生化分析

科研项目

1. 国家自然科学基金面上项目:等离子体共振能量转移智能光谱分析与高分辨散射成像应用研究(22274134);主持。

2. 重庆市自然科学基金面上项目:基于机器学习的等离子体光散射成像分析研究(cstc2021jcyj-msxmX0066);主持。

3. 重庆市教改项目:多学科融合与新工科背景下计算机视觉的教学方法探索与实践 yjg213033);主持。

近期代表性论著(不超过十项)

1. Zi Yu Pan; Cheng Zhi Huang; Lei Zhan*; Jun Zhou*, Plasmonic   Single Nanoparticle for Resonance Light Scattering Imaging Analysis and   Applications. Trac-Trend. Anal. Chem. 2023, 164, 117090.   (中科院1,   IF 14.908)

2. Zhang Quan Wu; Yun Peng Ma; Hui Liu*; Cheng Zhi Huang*; Jun Zhou*,   High Confidence Single Particle Analysis with Machine Learning. Anal.   Chem. 2023, 95, 15375-15383. (中科院1,   IF 8.008)

3. Ling Zhao; Yun Peng Ma; Shan Xiong Chen; Jun Zhou*; Multi-view   co-clustering with multi-similarity. Applied Intelligence 2023,   53, 16961-16972. (中科院2,   IF 5.019)

4. Ling Zhao; Yunpeng Ma; Shanxiong Chen; Jun Zhou*, In Deep   Double Self-Expressive Subspace Clustering, ICASSP 2023 - 2023 IEEE   International Conference on Acoustics, Speech and Signal Processing (ICASSP),   4-10 June 2023; pp 1-5. (CCF-B)

5. Tingting Leng; Ling Zhao; Xiaolong Xiong; Peng Cheng; Jun Zhou*,   Self-Expressive Network-Based Subspace Clustering for Deep Embedding. In The   26th European Conference on Artificial Intelligence (ECAI 2023,   Kraków, Poland, 2023; pp 1357 - 1364. (CCF-B)

6. Jun Zhou; Wei He; Hui Liu*; Cheng Zhi Huang*; Energy Flow during the   Plasmon Resonance-Driven Photocatalytic Reactions on Single Nanoparticles. ACS   Catal. 2022, 12, 847-853. (中科院1,   IF 13.7)

7. Ming Ke Song; Yun Peng Ma; Hui Liu; Ping Ping Hu; Cheng Zhi Huang*; and Jun   Zhou*; High Resolution of Plasmonic Resonance Scattering Imaging with   Deep Learning. Anal. Chem. 2022, 94, 4610-4616. (中科院1,   IF 8.008)

8. Jun Bo Luo; Jiao Chen; Hui Liu*; Cheng Zhi Huang*; Jun Zhou*;   High-efficiency synthesis of red carbon dots using machine learning. Chem.   Commun. 2022, 58, 9014-9017. (中科院2,   IF 6.222)