Niu Zhibin
Associate professor



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Personal Profile

Dr.Zhibin Niu is currently Associate Professor in the College of Intelligence and Computing at Tianjin University. He is a recipient of EU Marie Skłodowska-Curie Fellowship, Europe’s most competitive and prestigious awards.  

He has a mult-country study and research experience. He received his Ph.D. in Computer Sciences from Cardiff University, UK,  and he was lucky to be guided by Prof. Ralph Martin, Dr. Malcolm Sabin, and Dr.Frank Langbein. As a visiting researcher, he was also guided by Prof. Sara McMains, Prof. Vadim Shapiro at the University of California, Berkeley, US and Prof. Bert Juttler at Johannes Kepler University, Austria. He received his Master Degree in Computer Vision and Pattern Recognition from Shanghai Jiao Tong University, and Bachelor Degree in Automation from Tianjin University, China. 

His work leads the feature recognition time complexity from quadratic or exponential to linear, which is a significant breakthrough in this field.  European Commission recognize his approach as Highlighted Contributions. The core paper was listed by the top journal as one of the Most Downloaded Computer-Aided Design Articles; it was also endorsed by Airbus and Rolls-Royce. His current work mainly about Intelligence Visual Analytics and its interdisciplinary applications, such as in financial and energy domain. 


[1]. iConViz: Interactive Visual Exploration of the Default Contagion Risk of Networked-Guarantee Loans. IEEE VAST 2020.  (CCF-A)

[2]. Contagious Chain Risk Rating for Networked-guarantee Loans. ACM SIGKDD 2020. (CCF-A)

[3]. Retrospect and prospect of a section-based stratigraphic and palaeontological database – Geobiodiversity Database. Earth System Science Data, 2020. (IF=11.333, SCI Q1)

[4]. Rapidly Finding CAD Features Using Database Optimization. Computer-Aided Design. 2015. (SCI Q2, IF=3.072)

[5]. A flexible potential-flow model based high resolution spatiotemporal energy demand forecasting framework. Applied Energy. 2021. (SCI Q1, IF=9.746)

[6]. Wind turbine failure prediction and health assessment based on adaptive maximum mean discrepancy. International Journal of Electrical Power & Energy Systems. 2021 (SCI Q2, IF=4.63)

[7]. Dual-stage attention-based long-short-term memory neural networks for energy demand prediction. Energy and Buildings. 2021 (SCI Q2, IF=5.879)


彭劼扬   (2016-2023),博士(共同指导),发表SCI一区2篇,SCI二区2篇,2023年获批欧盟玛丽居里人才基金资助(资助率14%~15%)。

刘晗曦   (2023-2023),本科,天津大学优秀本科毕业论文。

潘耀华 (2019-2021),硕士,在读期间发表SCI二区期刊1篇,授权专利1项。


吴俊岐  (2018-2021),本科,在读期间发表SCI一区期刊2篇,授权专利1项,天津大学优秀本科毕业论文。

申小靖 (2018-2021),本科,天津大学智算学部优秀毕业论文。

我们在基于数据挖掘的多学科交叉领域(例如,智能金融,智能能源等)展开了广泛的研究,欢迎对大数据分析,数据挖掘,计算机视觉感兴趣的同学加入(智能学部,新媒体学院,深圳佐治亚学院均可),请联系 / 微信 wxv7015)

  • 我们崇尚多学科,多元文化融合,加入我们团队的优秀同学,无论本科还是研究生,在读期间均有机会,获得资助赴欧洲、美国或者日本的研究机构交流学习。

  • 我们崇尚做有价值,有影响力的工作,科研论文的质量比数量远远重要,加入我们团队的本科和研究生同学的代码能力、科研和论文表述能力均会得到很好的锻炼。

  • 我会尽最大可能为同学们提供优秀的科研环境和计算资源 (目前包括4*NVIDIA RTX8000的大型服务器~200G显存以及7台塔式GPU服务器)。

  • 我们不开大会,我们通过频繁1:1的师生沟通,发现和解决科研问题,推动科研。

Research Group

[1]Name of Research Group:Team

  • 杜佳
  • 张芳菲
  • 贾思源
  • 孟繁钥
  • 薛雅琪
  • 张智秋
  • 彭劼扬
  • 吴俊岐
  • 李泰均


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