WELCOME TO DR. N. ZENG's HOMEPAGE



Bio Sketch:

    Nianyin Zeng is currently a Professor with the Department of Instrumental and Electrical Engineering of Xiamen University. He received the B.Eng. degree in electrical engineering and automation in 2008 and the Ph.D. degree in electrical engineering in 2013, both from Fuzhou University. From October 2012 to March 2013, he was a RA in the Department of Electrical and Electronic Engineering, the University of Hong Kong. From September 2017 to August 2018, he was an ISEF Fellow founded by the Korea Foundation for Advance Studies and also a Visiting Professor at the Korea Advanced Institute of Science and Technology (KAIST).

    His current research interests include intelligent data analysis, machine learning and computer vision, computational intelligent, system modeling and applications. He has published more than 80 research papers in referred journal and conferences as well as 13 patents. By Google Scholar, his publications have been cited by more than 7,000 times with H-Index 34.

    Dr. Zeng is currently serving or has served as an Associate Editor for Neurocomputing Frontiers in Medical Technology, and Evolutionary Intelligence, an Editorial Board member for Computers in Biology and Medicine, Biomedical Engineering Online, Mathematical Problems in Engineering, Journal of Electronics & Information Technology, and Journal of Image and Graphics, and also Guest Editors for Frontiers in Neuroscience and Frontiers in Medical Technology. He has also served as program committee members for a number of premier international conferences related to intelligent data analysis, including EAI ICMTEL, ACAIT, ICCSE, etc.

    Dr. Zeng has received a number of prestigious awards, including High-Level Talent of Fujian Province, Key-Talent of Xiamen City, Nanqiang Young-Top-Talent of Xiamen University, three Provincial Natural Science Awards, Invention and Entrepreneurship Achievement Award by the China Invention Association, and Distinguished Reviewers of Computers in Biology and Medicine, Neurocomputing, and Chinese Journal of Scientific Instrument.



Research Areas:

  1. ◊  Intelligent Data Analysis
  2. ◊  Machine Learning and Computer Vision
  3. ◊  Computational Intelligent
  4. ◊  Artificial Intelligence in Biomedical and Industry



Education Background:

  1. ◊  2013 Fuzhou University, China Ph.D. in Electrical Engineering
  2. ◊  2008 Fuzhou University, China B. Eng in Electrical Engineering and Automation



Employment and Related:

  1. ◊  08/2023-present   Professor, Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen, China.
  2. ◊  08/2018-07/2023   Associate Professor, Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen, China.
  3. ◊  09/2017-08/2018  Visiting Professor, Department of Computer Science, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
  4. ◊  03/2014-07/2018  Assistant Professor, Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen, China.
  5. ◊  10/2012-03/2013  Research Assistant, Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China.



Research Grants:

  1. Has conducted more than 20 research projects funded by governmental and various industrial units such as:
  2. ◊  The Fundamental Research Funds for the Central Universities of China, Grant No. 20720220076, funded by Xiamen University, 2022--2024.
  3. ◊  National Natural Science Foundation of China, Grant No. 62073271, funded by National Natural Science Foundation of China, China, 2021--2024.
  4. ◊  The International Science and Technology Cooperation Project of Fujian Province of China, Grant No. 2019I0003, funded by Science and Technology Commission of Fujian Province, China, 2019--2021.
  5. ◊  The Fundamental Research Funds for the Central Universities of China, Grant No. 20720220076, funded by Xiamen University, 2019--2021.
  6. ◊  International Scholar Exchange Fellowship, funded by Korea Foundation for Advance Studies, 2017-2018.
  7. ◊  UK-China Industry Academia Partnership Programme, Grant No. UK-CIAPP-276, the XMU Principal Investigator, funded jointly by the Royal Academy of Engineering of the UK and the Chinese Academy of Engineering, 2017--2019.
  8. ◊  National Natural Science Foundation of China', Grant No. 61403319, funded by National Natural Science Foundation of China, China, 2015--2017.
  9. ◊  Fujian Natural Science Foundation', Grant No. 2015J05131, funded by Science and Technology Commission of Fujian Province, China, 2015--2018.



Professional Activities:

Associate Editors:
  1. Neurocomputing 2017-
  2. Frontiers in Medical Technology 2020-
  3. Evolutionary Intelligence 2020-

Editorial Board Members:
  1. Computers in Biology and Medicine 2017-
  2. Mathematical Problems in Engineering 2020-
  3. BioMedical Engineering OnLine 2015-2021
  4. Journal of Electronics & Information Technology 2021-
  5. Journal of Image and Graphics 2020-

Guest Editors:
  1. Frontiers in Neuroscience
  2. Frontiers in Medical Technology
  3. IEICE Transactions on Information and Systems
  4. Applied Sciences

Conference Organizing:
  1. Member of Program Committee of The 4th EAI International Conference on Multimedia Technology and Enhanced Learning (EAI ICMTEL 2022)
  2. Member of Program Committee of The 5th Asian Conference on Artificial Intelligence Technology (ACAIT 2021)
  3. Member of Program Committee of The 3rd EAI International Conference on Multimedia Technology and Enhanced Learning (EAI ICMTEL 2021)
  4. Invited Session Chair of The 12th International Conference on Computer Science and Education (ICCSE 2017)
  5. International Program Committee of The 11th International Conference on Computer Science and Education (ICCSE 2016)
  6. Technical Programme Committee of The 3rd International Conference on Biomedical Engineering and Biotechnology (ICBEB 2014)

Paper Reviewing:

       An active (exhausted!) reviewer for many international journals such as:   



Awards and Honours:

  1. ◊  08/2022  High-Level Talent of Fujian Province.
  2. ◊  08/2021  "Nanqiang" Young-Top-Talent of Xiamen University.
  3. ◊  11/2020  Second-Class Award of Invention and Entrepreneurship Achievement, China Invention Association.
  4. ◊  07/2020  Third-Class Award of Fujian Science and Technology.
  5. ◊  07/2020  First-Class Award of Chongqing Science and Technology.
  6. ◊  06/2019  Key-Talent of Xiamen City.
  7. ◊  06/2019  Hot Paper Award of Science China-Information Science.
  8. ◊  01/2018  Distinguished Reviewers 2017 of Neurocomputing.
  9. ◊  08/09/2017  Second-Class Award of Fujian Science and Technology.
  10. ◊  05/2017  International Scholar Exchange Fellowship, funded by Korea Foundation for Advance Studies.
  11. ◊  12/2016  Second-Class Award of The Outstanding Academic Papers of Fujian Province.
  12. ◊  01/2016  Distinguished Reviewers 2015 of Computers in Biology and Medicine.
  13. ◊  11/2011  Holder of the Top-Class Excellent Academic Scholarship at Fuzhou University, Fuzhou, China.
  14. ◊  06/2011  "Top Ten Academic Star" (Science and Technology category) of postgraduate student at Fuzhou University, Fuzhou, China.
  15. ◊  07/2008  Outstanding graduates of Fuzhou University, Fuzhou, China.



Selected Publications:

    Has published more than 80 papers in referred journal and conferences, as well as 13 patents. Has received more than 7,000 citations (H-Index:34) by Google Scholar.
  1. N. Zeng, P. Wu, Z. Wang, H. Li, W. Liu, X. Liu, "A small-sized object detection oriented multi-scale feature fusion approach with application to defect detection",IEEE Transactions on Instrumentation and Measurement, vol. 71, article no. 3507014, 2022.
  2. N. Zeng, Z. Wang, W. Liu, H. Zhang, K. Hone and X. Liu, "A dynamic neighborhood-based switching particle swarm optimization algorithm", IEEE Transactions on Cybernetics, vol. 52, no. 9, pp. 9290-9301, 2022.
  3. X. Luo, Y. Yuan, S. Chen, N. Zeng, Z. Wang, "Position-transitional particle swarm optimization-incorporated latent factor analysis", IEEE Transactions on Knowledge and Data Engineering, vol. 34, no. 8, pp. 3958-3970, 2022.
  4. H. Li,N. ZengP. Wu, K. Clawson, "Cov-Net: A computer-aided diagnosis method for recognizing COVID-19 from chest X-ray images via machine vision", Expert Systems With Applications, vol. 207, 118029, 2022.
  5. H. Li, J. Li, P. Wu, Y. You, N. Zeng, "A ranking-system-based switching particle swarm optimizer with dynamic learning strategies", Neurocomputing, vol. 494, pp. 356-367, 2022.
  6. P. Wu, H. Li,N. Zeng, F. Li, "FMD-Yolo: An efficient face mask detection method for COVID-19 prevention and control in public", Image and Vision Computing, vol. 117, 104341, 2022.
  7. M. Liu , J. Li , S. Li , N. Zeng, "Recurrent-Neural-Network-based Polynomial Noise Resistance Model for Computing Dynamic Nonlinear Equations Applied to Robotics", IEEE Transactions on Cognitive and Developmental Systems, doi: 10.1109/TCDS.2022.3159852.
  8. H. Li, P. Wu, N. Zeng, Y. Liu, Fuad E. Alsaadi, "A survey on parameter identification, state estimation and data analytics for lateral flow immunoassay: from systems science perspective", International Journal of Systems Science, https://doi.org/10.1080/00207721.2022.2083262.
  9. N. Zeng, H. Li, Y. Peng, "A new deep belief network-based multi-task learning for diagnosis of Alzheimer's disease", Neural Computing and Applications, https://doi.org/10.1007/s00521-021-06149-6.
  10. C. Huang, Y. Lan, G. Zhang, G. Xu, L. Jiang, N. Zeng, J. Tan, E. Y. K. NG, Y. Cheng, N. Han, R. Ji, Y. Peng, "A new transfer function for volume visualization of aortic stent and its application to virtual endoscopy", ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 16 (2020): 1 - 14.
  11. N. Zeng, D. Song, H. Li, Y. You, Y. Liu, F. Alsaadic, "A competitive mechanism integrated multi-objective whale optimization algorithm with differential evolution", Neurocomputing, vol. 432, pp. 170-182, 2021.
  12. N. Zeng, H. Li, Z. Wang, W. Liu, S. Liu, F. Alsaadi, X. Liu, "Deep-reinforcement-learning-based images segmentation for quantitative analysis of gold immunochromatographic strip", Neurocomputing, vol. 425, pp. 173-180, 2021.
  13. W. Liu, Z. Wang, Y. Yuan, N. Zeng, K. Hone, X. Liu, "A novel sigmoid-function-based adaptive weighted particle swarm optimizer", IEEE Transactions on Cybernetics, vol. 51, no. 2, pp. 1085-1093, 2021.
  14. C. Huang, Y. Lan, G. Xu, X. Zhai, J. Wu, F. Lin, N. Zeng, Q. Hong, E. Ng, Y. Peng, F. Chen, G. Zhang, "A deep segmentation network of multi-scale feature fusion based on attention mechanism for IVOCT lumen contour," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 18, no. 1, pp. 62-69, 2021
  15. L. Wang, Y. Jiao, Y. Qiao, N. Zeng, R. Yu, "A novel approach combined transfer learning and deep learning to predict TMB from histology image", Pattern Recognition Letters, vol. 135, pp. 244-248, 2020.
  16. N. Zeng, Z. Wang, H. Zhang, K.-E. Kim, Y. Li and X. Liu, "An improved particle filter with a novel hybrid proposal distribution for quantitative analysis of gold immunochromatographic strips", IEEE Transactions on Nanotechnology, vol. 18, no. 1, pp. 819-829, 2019.
  17. W. Liu, Z. Wang, X. Liu, N. Zeng, D. Bell, "A novel particle swarm optimization approach for patient clustering from emergency departments", IEEE Transactions on Evolutionary Computation, vol. 23, no. 4, pp. 632-644, 2019.
  18. N. Zeng, H. Qiu, Z. Wang, W. Liu, H. Zhang, Y. Li, "A new switching-delayed-PSO-based optimized SVM algorithm for diagnosis of Alzheimer's disease", Neurocomputing, vol. 320, pp. 195-202, 2018.
  19. N. Zeng, H. Zhang, B. Song, W. Liu, Y. Li, A. M. Dobaie, "Facial expression recognition via learning deep sparse autoencoders", Neurocomputing, vol. 273, pp. 643-649, 2018.
  20. N. Zeng, Y. You, L. Xie, H. Zhang, L. Ye, W. Hong, Y. Li, "A new imaged- based quantitative reader for the gold immunochromatographic assay", Optik, vol. 152, pp 92-99, 2018.
  21. N. Zeng, H. Zhang, W. Liu, J. Liang, F. E. Alsaadi, "A switching delayed PSO optimized extreme learning machine for short-term load forecasting", Neurocomputing, vol. 240, pp. 175-182, 2017.
  22. N. Zeng, H. Zhang, Y. Li, J. Liang, A. M. Dobaie, "Denoising and deblurring gold immunochromatographic strip images via gradient projection algorithms", Neurocomputing, vol. 247, pp. 165-172, 2017.
  23. N. Zeng, Z. Wang, H. Zhang, "Inferring nonlinear lateral flow immunoassay state-space models via an unscented Kalman filter", Science China Information Sciences, vol. 59, no. 11, 112204, 2016.
  24. N. Zeng, Z. Wang, H. Zhang, W. Liu, F. E. Alsaadi, "Deep belief networks for quantitative analysis of gold immunochromatographic strip", Cognitive Computation, vol. 8, no. 4, pp. 684-692, 2016.
  25. N. Zeng, Z. Wang, H. Zhang and F. E. Alsaadi, "A novel switching delayed PSO algorithm for estimating unknown parameters of lateral flow immunoassay", Cognitive Computation, vol. 8, no. 2, pp. 143-152, 2016.
  26. N. Zeng, H. Zhang, Y. Chen, B. Chen, Y. Liu, "Path planning for intelligent robot based on switching local evolutionary PSO algorithm", Assembly Automation, vol. 36, no. 2, pp. 120-126, 2016.
  27. N. Zeng, Z. Wang, B. Zineddin, Y. Li, M. Du, L. Xiao, X. Liu and T. Young, "Image-based quantitative analysis of gold immunochromatographic strip via cellular neural network approach", IEEE Transactions on Medical Imaging, vol. 33, no. 5, pp. 1129-1136, 2014.
  28. N. Zeng, Y. S. Hung, Y. Li, M. Du, "A novel switching local evolutionary PSO for quantitative analysis of lateral flow immunoassay", Expert Systems with Application, vol. 41, no. 4, pp.1708-1715, 2014.
  29. N. Zeng, Z. Wang, Y. Li, M. Du, J.Cao, X. Liu, "Time series modeling of nano-gold immunochromatographic assay via expectation maximization algorithm", IEEE Transactions on Biomedical Engineering, vol. 60, no. 12, pp. 3418-3424, 2013.
  30. N. Zeng, Z. Wang, Y. Li, M. Du, X. Liu, "A hybrid EKF and switching PSO algorithm for joint state and parameter estimation of lateral flow immunoassay models", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. 2, pp. 321-329, 2012.
  31. N. Zeng, Z. Wang, Y. Li, M. Du, X. Liu, "Identification of nonlinear lateral flow immunoassay state-space models via particle filter approach", IEEE Transactions on Nanotechnology, vol. 11, no. 2, pp.321-327, 2012.
  32. N. Zeng, Z. Wang, Y. Li, M. Du, X. Liu, "Inference of nonlinear state-space models for sandwich-type lateral flow immunoassay using extended Kalman filtering", IEEE Transactions on Biomedical Engineering, vol. 58, no. 7, pp. 1959-1966, 2011.

For more information can be referred to:

                     



Contact:
  1. Dr. Nianyin Zeng
  2. Department of Instrumental and Electrical Engineering
  3. Xiamen University
  1. Email: zny@xmu.edu.cn
  2. Webpage: https://isc.xmu.edu.cn/team/zny_en.htm
  3. Address: No. 4221-134, Xiangan South Road Xiamen, Fujian 361102, China