Dr. Jian Zhang is an Assistant Professor (Ph.D. Supervisor) at the School of Electronic and Computer Engineering (SECE), Peking University Shenzhen Graduate School, Shenzhen, China. He is now leading the Visual-Information Intelligent Learning LAB (VILLA). He is also a visiting scholar at Peng Cheng Laboratory.

His research interests include intelligent multimedia processing, computer vision and optimization. He has published over 80 technical articles in refereed international journals and proceedings, with more than 3000 citations [Google Scholar]. His SECE webpage in Chinese is here [中文主页].

He received the B.S. degree from the Department of Mathematics, Harbin Institute of Technology (HIT), Harbin, China, in 2007, and received his M.Eng. and Ph.D. degrees (under the supervision of Prof. Debin Zhao) from the School of Computer Science and Technology, HIT, in 2009 and 2014, respectively. From 2014 to 2018, he worked as a postdoctoral researcher at Peking University (PKU) (cooperated with Prof. Wen Gao), Hong Kong University of Science and Technology (HKUST) (cooperated with Prof. Xiaopeng Fan), and King Abdullah University of Science and Technology (KAUST) (cooperated with Prof. Bernard Ghanem).

张健,北京大学信息工程学院助理教授/研究员、博士生导师,深圳市海外高层次人才。分别于2007年、2009年、2014年获得哈尔滨工业大学(HIT)数学与应用数学理学学士、计算机科学与技术工学硕士及计算机应用工学博士。2014-2018年期间先后在北京大学(PKU)、香港科技大学(HKUST)和沙特阿卜杜拉国王科技大学(KAUST)做博士后访问研究。目前,他负责视觉信息智能学习课题组(Visual-Information Intelligent Learning LAB,简称 VILLA)。他也是 鹏城实验室的访问学者。

主要从事图像表示重建与计算机视觉方面的基础理论和应用研究,在 SPM / TPAMI / TIP / CVPR / ECCV / ICCV 等高水平国际期刊会议上发表论文90余篇。Google Scholar引用3728次,H-index值为29,SCI他引超过1800次(其中单篇第一作者期刊论文 Google Scholar最高引用600次;单篇第一作者会议论文 Google Scholar最高引用510次)。相关研究成果申请中国专利10余项。获得IEEE视觉通讯与图像处理(VCIP)国际会议2011年度最佳论文奖以及该国际会议2015年度最佳学生论文奖、IEEE多媒体IEEE MultiMedia国际期刊2018年度最佳论文奖、中国多媒体大会ChinaMM 2021年度最佳论文奖、深圳市科学技术协会2021年优秀自然科学学术论文奖(共16篇,信息领域唯一1篇)、2020及2021连续两年入选人工智能与图像处理领域全球前2%顶尖科学家"年度影响力"榜单。

欢迎优秀的本科生和硕士生保送和报考北京大学信息工程学院的硕士和博士研究生,课题组博士后职位也已开放,更多招生、实习以及科研最新信息请查看个人主页: https://jianzhang.tech/ 以及实验室主页: https://villa.jianzhang.tech/

Research Areas

  • Intelligent Multimedia Processing
  • Deep Learning and Optimization
  • Computer Vision

Awards

Publication