World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
83
Citations
27876
World Ranking
902
National Ranking
490

Overview

Yun Q. Shi is affiliated with the New Jersey Institute of Technology in the United States. Their research spans multiple scientific disciplines, with a focus on cognitive neuroscience, radiology, nuclear medicine and imaging, computer vision and pattern recognition, organic chemistry, and experimental and cognitive psychology.

Their scholarly output includes work published in several venues, notably:

  • arXiv (Cornell University)
  • Journal of Affective Disorders
  • Advanced Materials
  • China Journal of Accounting Research
  • Human Brain Mapping

Yun Q. Shi has collaborated frequently with peers including Peishan Dai, Zhongchao Huang, Ying Zhou, Da Lu, and Zailiang Chen.

Their research covers a variety of principal topics, such as:

  • Functional Brain Connectivity Studies
  • Mental Health Research Topics
  • EEG and Brain-Computer Interfaces
  • Synthesis and Biological Evaluation
  • Advanced MRI Techniques and Applications
  • Advanced Neuroimaging Techniques and Applications
  • Blockchain Technology Applications and Security

Recent papers authored or coauthored by Yun Q. Shi include:

  • "Can blockchain technology be effectively integrated into the real economy? Evidence from corporate investment efficiency," 2023, China Journal of Accounting Research
  • "Potassium doping carbon nitride: Dramatically enhanced photocatalytic properties for hydroxyalkylation of quinoxalin-2(1H)-ones with alcohol under air atmosphere," 2022, Journal of Catalysis
  • "Classification of MDD using a Transformer classifier with large-scale multisite resting-state fMRI data," 2023, Human Brain Mapping
  • "Classification of recurrent major depressive disorder using a new time series feature extraction method through multisite rs-fMRI data," 2023, Journal of Affective Disorders
  • "Classification of recurrent major depressive disorder using a residual denoising autoencoder framework: Insights from large-scale multisite fMRI data," 2024, Computer Methods and Programs in Biomedicine

Best Publications

  • Reversible data hiding

    Zhicheng Ni;Yun-Qing Shi;N. Ansari;Wei Su

  • Reversible Watermarking Algorithm Using Sorting and Prediction

    V. Sachnev;Hyoung Joong Kim;Jeho Nam;S. Suresh

  • Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards

    Yun Q. Shi;Huifang Sun

  • Reversible Data Hiding: Advances in the Past Two Decades

    Yun-Qing Shi;Xiaolong Li;Xinpeng Zhang;Hao-Tian Wu

  • A survey on image steganography and steganalysis

    Bin Li;Junhui He;Jiwu Huang;Yun Qing Shi

  • Pairwise Prediction-Error Expansion for Efficient Reversible Data Hiding

    Bo Ou;Xiaolong Li;Yao Zhao;Rongrong Ni

  • A DWT-DFT composite watermarking scheme robust to both affine transform and JPEG compression

    Xiangui Kang;Jiwu Huang;Yun Q Shi;Yan Lin

  • A Markov process based approach to effective attacking JPEG steganography

    Yun Q. Shi;Chunhua Chen;Wen Chen

  • Embedding image watermarks in dc components

    Jiwu Huang;Y.Q. Shi;Yi Shi

  • A Novel Difference Expansion Transform for Reversible Data Embedding

    Hyoung Joong Kim;V. Sachnev;Yun Qing Shi;Jeho Nam

  • Distortionless data hiding based on integer wavelet transform

    Guorong Xuan;Jiang Zhu;Jidong Chen;Yun Q. Shi

  • A generalized Benford's law for JPEG coefficients and its applications in image forensics

    Dongdong Fu;Yun Q. Shi;Wei Su

  • Efficiently self-synchronized audio watermarking for assured audio data transmission

    Shaoquan Wu;Jiwu Huang;Daren Huang;Y.Q. Shi

  • Uniform Embedding for Efficient JPEG Steganography

    Linjie Guo;Jiangqun Ni;Yun Qing Shi

  • JPEG image steganalysis utilizing both intrablock and interblock correlations

    Chunhua Chen;Y.Q. Shi

  • Using Statistical Image Model for JPEG Steganography: Uniform Embedding Revisited

    Linjie Guo;Jiangqun Ni;Wenkang Su;Chengpei Tang

  • Distance-reciprocal distortion measure for binary document images

    Haiping Lu;A.C. Kot;Y.Q. Shi

  • Robust Lossless Image Data Hiding Designed for Semi-Fragile Image Authentication

    Zhicheng Ni;Y.Q. Shi;N. Ansari;Wei Su

  • A natural image model approach to splicing detection

    Yun Q. Shi;Chunhua Chen;Wen Chen

  • Steganalysis based on multiple features formed by statistical moments of wavelet characteristic functions

    Guorong Xuan;Yun Q. Shi;Jianjiong Gao;Dekun Zou

  • Reversible data hiding

    Zhicheng Ni;Y.Q. Shi;N. Ansari;Wei Su

Frequent Co-Authors

Jiwu Huang
Jiwu Huang Shenzhen University
Wei Su
Wei Su Tianjin University
Nirwan Ansari
Nirwan Ansari New Jersey Institute of Technology
Jianjiong Gao
Jianjiong Gao Memorial Sloan Kettering Cancer Center
Hyoung Joong Kim
Hyoung Joong Kim Korea University
Alex C. Kot
Alex C. Kot Nanyang Technological University
Frank Y. Shih
Frank Y. Shih New Jersey Institute of Technology
Anthony Vetro
Anthony Vetro Mitsubishi Electric (United States)
Yao Zhao
Yao Zhao Beijing Jiaotong University
Stefan Katzenbeisser
Stefan Katzenbeisser University of Passau

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