Chun-Qi Chang, Ph.D.

Investigator, Shenzhen Institute of Neuroscience
Email: cqchang@sions.cn

Professor Chunqi Chang, Investigator of Shenzhen Institute of Neuroscience, Professor of Shenzhen University, Member of Thousand Talents Program (Youth). In 1987 he enrolled the Special Class for Gifted Young of University of Science and Technology of China (USTC), where he was awarded Bachelor (1992) and Master (1995) degrees from Department of Electronic Engineering and Information Sciences, and in 2001 he was awarded PhD degree from the University of Hong Kong (HKU). He was with HKU from 2002 to 2012, serving as Postdoctoral Fellow, Research Associate, Research Assistant Professor in the Department of Electrical and Electronic Engineering, and Visiting Professor of Department of Linguistics and National Key Laboratory of Brain and Cognitive Sciences. From 2012 to 2015, he was with School of Electronic and Information Engineering, Suzhou University. In May 2015, he joined School of Biomedical Engineering, Shenzhen University. His research is in the broad areas of signal processing, biomedical engineering, computational systems biology, and brain and cognitive sciences, and his main research interests include neuroimaging, neuroinformatics, neuroengineering, and machine learning. His research has been supported by fundings from RGC and ITF of Hong Kong, and NSF and 973 of China. He has published over 100 research papers on international journals and conference proceedings, over 40 of which included in SCI.

Selected Publications:

  1. Dai, J., Bao, X., Hu, N., Chang, C., & Xu, W. (2014). A Recursive RARE Algorithm for DOA Estimation With Unknown Mutual Coupling. Antennas and Wireless Propagation Letters, IEEE, 13, 1593-1596.
  2. Dai, J., & Chang, C. (2014). Power allocation for maximizing the MAC capacity via majorization. EURASIP Journal on Advances in Signal Processing, 2014(1), 1-9.
  3. Zhu, L., Nie, Y., Chang, C., Gao, J. H., & Niu, Z. (2014). Different patterns and development characteristics of processing written logographic characters and alphabetic words: An ALE meta‐analysis. Human Brain Mapping, 35(6), 2607-2618.
  4. Dai, J., Chang, C., Mai, F., Zhao, D., & Xu, W. (2013). On the SVMpath singularity. Neural Networks and Learning Systems, IEEE Transactions on ,24(11), 1736-1748.
  5. Tam, G. H. F., Chang, C., & Hung, Y. S. (2013). Gene regulatory network discovery using pairwise Granger causality. IET Systems Biology, 7(5), 195-204.
  6. Tan, L. H., Xu, M., Chang, C.Q., & Siok, W. T. (2013). China’s language input system in the digital age affects children’s reading development. Proceedings of the National Academy of Sciences, 110(3), 1119-1123.
  7. Xia, Z., Zhou, X., Chen, W., & Chang, C. (2010, December). A graph-based elastic net for variable selection and module identification for genomic data analysis. In Bioinformatics and Biomedicine (BIBM), 2010 IEEE International Conference on (pp. 357-362). IEEE.
  8. Jacklin, N., Ding, Z., Chen, W., & Chang, C. (2012). Noniterative convex optimization methods for network component analysis. Computational Biology and Bioinformatics, IEEE/ACM Transactions on, 9(5), 1472-1481.
  9. Lin, L., Shen, M., So, H. C., & Chang, C. (2012). Convergence analysis for initial condition estimation in coupled map lattice systems. IEEE Transactions on Signal Processing, 60(8), 4426-4432.
  10. Dai, J., Chang, C., Xu, W., & Ye, Z. (2012). Linear precoder optimization for MIMO systems with joint power constraints. IEEE Transactions on Communications, 60(8), 2240-2254.
  11. Mai, F., Chang, C. Q., & Hung, Y. S. (2011). A subspace approach for matching 2D shapes under affine distortions. Pattern Recognition, 44(2), 210-221.
  12. Guo, X., Chang, C., & Lam, E. Y. (2010). Blind separation of electron paramagnetic resonance signals using diversity minimization. Journal of Magnetic Resonance, 204(1), 26-36.
  13. Shen, M., Lin, L., Chen, J., & Chang, C. Q. (2010). A prediction approach for multichannel EEG signals modeling using local wavelet SVM. IEEE Transactions on Instrumentation and Measurement, 59(5), 1485-1492.
  14. Dai, J., Chang, C., Ye, Z., & Hung, Y. S. (2009). An efficient greedy scheduler for zero-forcing dirty-paper coding. IEEE Transactions on Communications, 57(7), 1939-1943.
  15. Chang, C., Ding, Z., Hung, Y. S., & Fung, P. C. W. (2008). Fast network component analysis (FastNCA) for gene regulatory network reconstruction from microarray data. Bioinformatics, 24(11), 1349-1358.
  16. Xu, W., Chang, C., Hung, Y. S., & Fung, P. C. W. (2008). Asymptotic properties of order statistics correlation coefficient in the normal cases. IEEE Transactions on Signal Processing,56(6), 2239-2248.
  17. Xu, W., Chang, C., Hung, Y. S., Kwan, S. K., & Fung, P. C. W. (2007). Order statistics correlation coefficient as a novel association measurement with applications to biosignal analysis., IEEE Transactions on Signal Processing, 55(12), 5552-5563.
  18. Chang, C., Ren, J., Fung, P. C., Hung, Y. S., Shen, J. G., & Chan, F. H. (2005). Novel sparse component analysis approach to free radical EPR spectra decomposition. Journal of Magnetic Resonance, 175(2), 242-255.
  19. Chang, C, Ding, Z., Yau, S. F., & Chan, F. H. (2000). A matrix-pencil approach to blind separation of colored nonstationary signals. IEEE Transactions on Signal Processing, 48(3), 900-907.
  20. Chang, C., Yau, S. F., Kwok, P., Chan, F. H., & Lam, F. K. (1999). Uncorrelated component analysis for blind source separation. Circuits, Systems and Signal Processing, 18(3), 225-239.