• 美国/伊利诺伊州/厄本那-香槟
    伊利诺伊大学厄本那-香槟分校
    电气与计算机工程博士
    2015/01-目前
    美国电气与计算机工程研究生申请、本科低GPA/转专业申请
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伊利诺伊大学厄本那-香槟分校电气与计算机工程博士(PhD in Electrical and Computer Engineering)

得克萨斯大学阿灵顿分校计算机科学硕士(MS in Computer Science)

华中科技大学模式识别与智能系统硕士(MS in Pattern Recognition & Intelligent System)

华中科技大学工程力学学士(B.Eng in Engineering Mechanics)

助教经历

Teaching Assistant: Algorithms & Data Structures 2014 Summer

  • Department of Computer Science and Engineering, UT Arlington

Teaching Assistant: Linear Algebra for Computer Science 2012 Fall, 2013 Spring, 2013 Fall, 2014 Spring, 2014 Fall

  • Department of Computer Science and Engineering, UT Arlington

Teaching Assistant: Introduction to Signal Processing 2014 Spring

  • Department of Computer Science and Engineering, UT Arlington

Teaching Assistant: Computational Methods 2012 Fall, 2013 Fall, 2014 Fall

  • Department of Computer Science and Engineering, UT Arlington

助研经历

Graduate Research student (with Prof. Minh N. Do) 01.2015 – present

  • Coordinated Science Laboratory, UIUC Urbana, IL, USA

Research Intern (with Dr. Oliver Wang and Dr. Eli Shechtman) 05.2016 – 08.2016 Adobe Creative Technology Lab Seattle, WA, USA

Research Intern (with Dr. Jue Wang) 05.2015 – 08.2015 Adobe Creative Technology Lab Seattle, WA, USA

Graduate Research student (with Prof. Junzhou Huang) 01.2012 – 12.2014 Department of Computer Science, UT Arlington Arlington, TX, USA

Research Intern (with Dr. Haitao Li) 08.2009 – 07.2010 Chinese Academy of Surveying and Mapping Beijing, China

Graduate Research student (with Prof. Yihua Tan and Jinwen Tian) 12.2008 – 03.2011 Institute for Pattern Recognition and Artificial Intelligence, HUST Wuhan, China

发文(JOURNAL PUBLICATIONS AND BOOK CHAPTERS)

  • Jiayi Ma, Chen Chen, Chang Li, Jun Huang, ”Infrared and visible image fusion via gradient transfer and total variation minimization”, Information Fusion, Volume 31, pp. 100-109, 2016.
  • Yong Ma, Jun Chen, Chen Chen, Fan Fan, Jiayi Ma, ”Infrared and visible image fusion using total variation model”, Neurocomputing, 2016.
  • Yihua Tan, Yansheng Li, Chen Chen, Jin-gang Yu and Jinwen Tian, ”Cauchy graph embedding based diffusion model for salient object detection”, JOSA A, Volume 33, Issue 5, pp. 887-898, 2016.
  • Chen Chen, Yeqing Li, Leon Axel and Junzhou Huang, ”Real Time Dynamic MRI by Exploiting Spatial and Temporal Sparsity with Dynamic Total Variation”, Magnetic Resonance Imaging, Volume 34, Issue 4, pp. 473-482, 2016.
  • Chen Chen, Yeqing Li, Wei Liu and Junzhou Huang, ”SIRF: Simultaneous Satellite Image Registration and Fusion in a Unified Framework”, IEEE Transactions on Image Processing (TIP), Volume 24, Issue 11, pp. 4213-4224, 2015.
  • Chen Chen, Fenghua Tian, Hanli Liu, and Junzhou Huang, ”Diffuse optical tomography enhanced by clustered sparsity for functional brain imaging”, IEEE Transactions on Medical Imaging (TMI), Volume 33, Issue 12, pp. 2323-2331, 2014.
  • Chen Chen, Yeqing Li and Junzhou Huang, ”Forest Sparsity for Multi-channel Compressive Sensing”, IEEE Transactions on Signal Processing (TSP), Volume 62, Issue 11, pp. 2803-2813, 2014.
  • Chen Chen and Junzhou Huang, ”The Benefit of Tree Sparsity in Accelerated MRI”, Medical Image Analysis, Volume 18, Issue 6, pp. 834-842, 2014.
  • Junzhou Huang, Chen Chen and Leon Axel, ”Fast Multi-contrast MRI Reconstruction”, Magnetic Resonance Imaging, Volume 32, Issue 10, pp. 1344-1352, 2014.
  • Chen Chen and Junzhou Huang, ”Exploiting the wavelet structure in Compressed Sensing MRI”, Magnetic Resonance Imaging, Volume 32, Issue 10, pp. 1377-1389, 2014.
  • Junzhou Huang, Chen Chen and Xinyi Cui, ”Sparsity Driven Background Modeling and Foreground Detection”, book chapter, in ”Background Modeling and Foreground Detection for Video Surveillance”, CRC Press, 2014.
  • Chen Chen, Yihua Tan, Haitao Li and Haiyan Gu, ”A Fast and Automatic Parallel Algorithm of Remote Sensing Image Mosaic”, Microelectronics & Computer, Volume 28, Issue 3, pp. 59-62, 2011.
  • Huabing Zhou, Dazhi Zhang, Chen Chen and Jinwen Tian, ”Discarding wide baseline mismatches with global and local transformation consistency”, Electronics letters, Volume 47, Issue 1, pp. 25-26, 2011.

全民CS,转专业、低GPA、春申全中?与CE、EE相较,申请难度与就业差别