PeopleofSuperintelligence

Researcher

Linlin Shen

Also known as 沈琳琳

Linlin Shen is a computer vision researcher at Shenzhen University whose work covers face recognition, deep learning theory and medical image analysis. They completed a PhD at the University of Nottingham in 2005 with a thesis on Gabor wavelets for face recognition, and published a review of Gabor-based face recognition in 2006. Their cell classification algorithm won the ICIP 2013 and ICPR 2016 contests, and Elsevier named them a Highly Cited Chinese Researcher in computer science every year from 2015 to 2023. In 2018 they published a skin lesion analysis network in Sensors, and in 2020 they coauthored the WaveCNets paper at CVPR. They are a professor at Shenzhen University, where they direct the Institute of Computer Vision and serve as deputy director of the National Engineering Laboratory for Big Data System Computing Technology.

Timeline

  1. 2005

    A Nottingham PhD on Gabor faces

    After a BSc and MEng at Shanghai Jiao Tong University, Shen completes a PhD at the University of Nottingham, funded by a UK government overseas research grant. The 2005 thesis, Recognizing Faces -- An Approach Based on Gabor Wavelets, is supervised by Li Bai in the School of Computer Science. Shen also works as a Research Fellow at Nottingham on MRI brain image processing.

  2. 2006

    A review of Gabor face recognition

    In October 2006, Shen and Li Bai publish A review on Gabor wavelets for face recognition in Pattern Analysis and Applications. The paper surveys 2D face recognition algorithms that use Gabor wavelets for feature extraction.

  3. 2013–2016

    Winning cell image contests

    Shen's cell classification algorithm wins first place at the ICIP 2013 and ICPR 2016 international cell image classification competitions.

  4. 2015–2023

    A Highly Cited Chinese Researcher

    Elsevier names Shen a Highly Cited Chinese Researcher in Computer Science every year from 2015 to 2023. Its 2016 list of Chinese Most Cited Researchers includes Shen as a professor at Shenzhen University.

  5. 2018

    Skin lesions and cell nuclei

    In February 2018, Shen and Yuexiang Li publish a Sensors paper on skin lesion analysis that uses two fully convolutional residual networks; on the ISIC 2017 dataset it reaches 0.753, 0.848 and 0.912 on three tasks. A target detection algorithm from Shen's group takes third place in the MICCAI 2018 Cell Nucleus Detection Competition.

  6. 2020

    Wavelet CNNs at CVPR

    At CVPR 2020, Shen presents WaveCNets with Qiufu Li, Sheng Guo and Zhihui Lai. The networks replace max-pooling, strided convolution and average-pooling with discrete wavelet transform layers, and the wavelet versions of VGG, ResNets and DenseNet reach higher accuracy and better noise-robustness on ImageNet and ImageNet-C.

  7. As of October 2026

    Professor at Shenzhen University

    Shen is a professor and doctoral supervisor in computer vision at Shenzhen University, where they direct the Institute of Computer Vision and serve as deputy director of the National Engineering Laboratory for Big Data System Computing Technology. Their research covers deep learning theory, face recognition and analysis, and medical image analysis, and their face recognition system has been used at the Hangzhou G20 Summit. They are also Co-Editor-in-Chief of Cognitive Computation and Systems and a computer vision algorithm consultant for Huawei.

Career

  1. NowShenzhen UniversityProfessor
  2. University of NottinghamResearch Fellow

Education

  1. 2005University of NottinghamPhD
  2. Shanghai Jiao Tong UniversityBSc

From the biography.

  1. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Shenzhen University. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  2. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Nottingham. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  3. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorateIncludes Shanghai Jiao Tong University. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorate. Across 2,116 people with both an undergraduate degree and a doctorate recorded, we trace which undergraduate schools feed which doctoral programs, how often students stay at the same school, and how paths differ by birth-country region.
  4. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Shanghai Jiao Tong University. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Linlin Shen yet. Send us a free-licensed photo.

  1. Recognizing Faces -- An Approach Based on Gabor Wavelets eprints.nottingham.ac.uk. Checked 21 October 2026.
  2. Linlin Shen, School of Artificial Intelligence, Shenzhen University ai.szu.edu.cn. Checked 21 October 2026.
  3. programs, CBMS 2020 2020.cbms-conference.org. Checked 21 October 2026.
  4. A review on Gabor wavelets for face recognition research.nottingham.edu.cn. Checked 21 October 2026.
  5. Good News in 2017, CCF Technical Committee on Computer Vision ccfcv.ccf.org.cn. Checked 21 October 2026.
  6. Skin lesion analysis towards melanoma detection using deep learning network research.nottingham.edu.cn. Checked 21 October 2026.
  7. Wavelet Integrated CNNs for Noise-Robust Image Classification, CVPR 2020 Open Access Repository openaccess.thecvf.com. Checked 21 October 2026.
  8. [2005.03337] Wavelet Integrated CNNs for Noise-Robust Image Classification arxiv.org. Checked 21 October 2026.