Personal profile
Gender: male
Degrees: Doctor
Title: Professor
E-mail: jjz01@bjut.edu.cn
Current Professional Societies:
Director of China Institute of Artificial Intelligence, Senior member of China Computer Federation
Research Areas:
Biological information Mining, Machine Learning, computational intelligence, brain science
Honors:
Prize of Outstanding Contribution to Graduate Education in Beijing University of Technology
Publications
1 Jinduo Liu, Junzhong Ji*, Guangxu Xun, Liuyi Yao, Mengdi Huai, Aidong Zhang， EC-GAN: Inferring Brain Effective Connectivity via Generative Adversarial Networks，Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20， CCF A), New York, USA, 2020-2-7至2020-2-12.
2 Junzhong Ji, YaoYao, Convolutional Neural Network with Graphical Lasso to Extract Sparse Topological Features for Brain Disease Classification, IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press.
3 Cuicui Yang, Junzhong Ji* and Sanjiang Li Stability Analysis of Chemotaxis Dynamics in Bacterial Foraging Optimization over Multi-dimensional Objective Functions, Soft Computing, 2020, 24(5), 3711-3725
4 Jinduo Liu, Junzhong Ji, Xiuqin Jia, Aidong Zhang Learning Brain Effective Connectivity Network Structure using Ant Colony Optimization Combining with Voxel Activation Information, IEEE Journal of Biomedical and Health Informatics (J-BHI）, DOI: 10.1109/JBHI.2019. 2946676, in press.
5 Junzhong Ji, Jinduo Liu, Aixiao Zou, Aidong Zhang ACOEC-FD: Ant Colony Optimization for learning Brain Effective connectivity networks from Functional MRI and Diffusion tensor imaging，Frontiers in Neuroscience，2019, 13,1290
6 Zhao Xuewu, Junzhong Ji* and Xing Wang Dynamic Brain Functional Parcellation via Sliding Window and Artificial Bee Colony Algorithm, Applied Intelligence, 2019, 49(5), 1748-1770
7 Zhao Xuewu, Junzhong Ji* and Aidong Zhang Artificial bee colony clustering with self-adaptive crossover and stepwise search for brain functional parcellation in fMRI data, Soft Computing, 2019，23(18), 8689-8709.
7 Jinduo Liu, Junzhong Ji, Liuyi Yao, and Aidong Zhang. Estimating Brain Effective Connectivity in fMRI Data by Non-stationary Dynamic Bayesian Networks, IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2019), 2019. San Diego, CA,, USA,11.18-21, 834-839, 2019（CCF B）
8 Junwei Li, Junzhong Ji, Yin Liang, Xiaodan Zhang, and Zihan Wang, Deep Forest with Cross-shaped Window Scanning Mechanism to Extract Topological Features, IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2019)，San Diego, CA,, USA,11.18-21, 688-691, 2019（CCF B ）
9 Zhihui Chen, Junzhong Ji, and Yin Liang, Convolutional Neural Network with an Element-wise Filter to Classify Dynamic Functional Connectivity, IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2019), San Diego, CA,, USA,11.18-21, 643-646, 2019（CCF B ）
10 Cuicui Yang, Junzhong Ji* and Aidong Zhang. BFO-FMD: Bacterial Foraging Optimization for Functional Module Detection in Protein-Protein Interaction Networks, Soft Computing, 2018，22(10), 3395-3416.
11 Xinying Xing, Junzhong Ji, and Yao Yao, Convolutional Neural Network with Element-wise Filters to Extract Hierarchical Topological Features for Brain Networks，2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 780-783.（CCF B）
12 J. Z. Ji, C. C. Yang, J. M. Liu and B C Yin. Comparative Study on Swarm Intelligence for Structure Learning of Bayesian Networks, Soft Computing, 2017，21(22), 6713-6738.
13 C. C. Yang, J. Z. Ji, J. M. Liu，J. D. Liu，and B C Yin. Structural Learning of Bayesian Networks by Bacterial Foraging Optimization, International Journal of Approximate Reasoning. 2016, 69: 147–167.
14 C. C. Yang, J. Z. Ji, J. M. Liu and B C Yin. Bacterial Foraging Optimization Using Novel Chemotaxis and Conjugation Strategies，Information Sciences, 363 (2016): 72-95.
15 Ji Junzhong*, Lv J. W, Yang C. C. and Zhang A. D.，Detecting Functional Modules Based on a Multiple-Grain Model in Large-Scale Protein-Protein Interaction Networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics，2016, 13(4): 610- 622 .
16 Junzhong Ji, Jinduo Liu, Peipeng Liang and Aidong Zhang，Learning Effective Connectivity Network Structure from fMRI Data Based on Artificial Immune Algorithm. PLoS ONE, 2016,11(4): e0152600.
17 J. Z. Ji, L Jiao, C. C. Yang and J. M. Liu. A Multi-Agent Evolutionary Method for Detecting Communities in Complex Networks, Computational Intelligence，2016, 32(4): 587- 614.
18 Yanbin Wang, Junzhong Ji, Peipeng Liang. Feature selection of fMRI data based on normalized mutual information and fisher discriminant ratio, Journal of X-ray Science and Technology，2016, 24(3): 467-475.
19 Cuicui Yang, Junzhong Ji, and Aidong Zhang, Bacterial Biological Mechanisms for Functional Module Detection in PPI Networks，2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 318-323.（CCF B）
20 Jinduo Liu, Junzhong Ji, Aidong Zhang, and Peipeng Liang, An ant colony optimization algorithm for learning brain effective connectivity network from fMRI data, 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 360-367.（CCF B）
21 J. Z. Ji, H X Liu, A. D. Zhang, Z J Liu and C. N. Liu. ACC-FMD: Ant Colony Clustering for Functional Module Detection in Protein-Protein Interaction Networks, International Journal of Data Mining and Bioinformatics. 2015, 11(3): 331–363.
22 J. Z. Ji, A. D. Zhang, C. N. Liu, X. M. Quan and Z. J. Liu. Survey: Functional Module Detection for Protein-Protein Interaction Networks, IEEE Transactions on Knowledge and Data Engineering. 2014, 26(2): 261-277. (CCF A)
23 J. Z. Ji, L Jiao, C. C. Yang and A. D. Zhang. MAE-FMD: Multi-Agent Evolutionary Method for Detecting Functional Modules in Protein-Protein Interaction Networks, BMC Bioinformatics，2014, 15:325
24 J. Z. Ji, H.K. Wei, C. N. Liu. An artificial bee colony algorithm for learning Bayesian networks，Soft Computing，2013，17（6）：983-994.
25 J. Z. Ji, X J Song, C. N. Liu and X. Z. Zhang. Ant Colony Clustering with Fitness Perception and Pheromone Diffusion for Community Detection in Complex Networks, Physica A: Statistical Mechanics and its Applications，2013，392（15）：3260-3272.
26 J. Z. Ji, Z J Liu, A. D. Zhang, C. C. Yang and C. N. Liu. HAM-FMD: Mining Functional Modules in Protein-Protein Interaction Networks Using Ant Colony Optimization and Multi-Agent Evolution, Neurocomputing, 2013，121，453-469.
27 J. Z. Ji,, R. B. Hu, H. X. Zhang, C. N. Liu. A Hybrid Method for Learning the Bayesian Networks Based on Ant Colony Optimization, Applied Soft Computing. 2011，11（4）：3373-3384.
Personal Statement:
Dr. Ji Junzhong has presided over several National Natural Science Fund projects, and published several papers on journals such as TKDE、JBHI、Information Sciences、 AAAI、and BIBM.
