Shusen Zhou

Shusen Zhou

Teacher

Ludong University

Contact

Personal Profile

Zhou Shusen is an Associate Professor and Master's Supervisor at the School of Computer Science and Artificial Intelligence, Ludong University. He received his Ph.D. in Computer Application Technology from Harbin Institute of Technology. His teaching portfolio includes undergraduate courses such as Introduction to Neuroscience and Deep Learning, as well as graduate-level courses including Machine Learning and Bioinformatics. He has published four papers on educational reform.

Dr. Zhou has led one project funded by the National Natural Science Foundation of China. He has authored over 30 research papers in reputable international journals such as EAAI (Expert Systems with Applications) and TCBB (IEEE/ACM Transactions on Computational Biology and Bioinformatics), and in proceedings of major conferences including ICPR, ICIP, ICDAR, and COLING. He holds more than 20 authorized national invention patents and has published one academic monograph.

His research lies at the intersection of bioinformatics and deep learning, with current interests focusing on:

1. Single-cell Genomics: Cell annotation and clustering, pseudo-time series analysis, trajectory inference for cellular differentiation, and cross-modal data integration.

2. Genomic Function Prediction: Feature extraction and functional prediction from DNA and RNA sequences, as well as protein function prediction.

3. Medical Big Data Analytics: Utilizing genetic testing for precise prediction of individual cancer risk, and integrating patient genomic information to support personalized treatment strategies.

He actively recruits master's students for both the Academic Master's program in Computer Science and Technology and the Professional Master's program in Electronic Information (with a focus on Artificial Intelligence) at Ludong University. Candidates with a strong interest in applying deep learning to bioinformatics are encouraged to reach out.

Personal Website: http://zhouss.cn/cn

Email: zhoushusen@ldu.edu.cn

QQ: 270747473

Research Project

[1] 2014.01-2016.12, National Natural Science Foundation of China, Study on Image Classification with Deep Belief Networks.

Published Paper

[1] Junjiang Liu, Shusen Zhou*, Mujun Zang, Chanjuan Liu, Tong Liu and Qingjun Wang. Multimodality based deep learning method for cancer-related T-cell receptor sequence prediction. Engineering Applications of Artificial Intelligence, 162, pp: 112318, 2025. (SCI, IF: 8.0)

[2] Junjiang Liu, Shusen Zhou*, Mujun Zang, Chanjuan Liu, Tong Liu and Qingjun Wang. Parallel convolutional and Transformer encoder method for cancer related T cell receptor sequences prediction. Applied Soft Computing, 183, pp: 113681, 2025. (SCI, IF: 6.6)

[3] Xindi Yu, Shusen Zhou*, Mujun Zang, Qingjun Wang, Chanjuan Liu, Tong Liu. Parallel convolutional contrastive learning method for enzyme function prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 21(6), pp: 2604-2609, 2024. (SCI, IF: 4.5)

[4] Junjiang Liu, Shusen Zhou*, Jing Ma, Mujun Zang, Chanjuan Liu, Tong Liu and Qingjun Wang. Graph attention network with convolutional layer for predicting gene regulations from single-cell ribonucleic acid sequence data. Engineering Applications of Artificial Intelligence, 136, pp: 108938, 2024. (SCI, IF: 7.5)

[5] Minglie Li, Shusen Zhou*, Tong Liu, Chanjuan Liu, Mujun Zang and Qingjun Wang. TSVM: transfer support vector machine for predicting MPRA validated regulatory variants. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 21(3), pp: 472-479, 2024. (SCI, IF: 4.5)

[6] Zhengsen Pan, Shusen Zhou*, Tong Liu, Chanjuan Liu, Mujun Zang and Qingjun Wang. WVDL: weighted voting deep learning model for predicting RNA-protein binding sites. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 20(5), pp: 3322-3328, 2023. (SCI, IF: 4.5)

[7] Zhengsen Pan, Shusen Zhou*, Hailin Zou, Chanjuan Liu, Mujun Zang, Tong Liu and Qingjun Wang. MCNN: multiple convolutional neural networks for RNA-protein binding sites prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 20(2), pp: 1180-1187, 2023. (SCI, IF: 4.5)

[8] Zhengsen Pan, Shusen Zhou*, Hailin Zou, Chanjuan Liu, Mujun Zang, Tong Liu and Qingjun Wang. CRMSNet: a deep learning model that uses convolution and residual multi-head self-attention block to predict RBPs for RNA sequence. Proteins, 91(8) , pp: 1032-1041, 2023. (SCI, IF: 4.088)

[9] Xindi Yu, Shusen Zhou*, Hailin Zou, Qingjun Wang, Chanjuan Liu, Mujun Zang and Tong Liu. Survey of deep learning techniques for disease prediction based on omics data. Human Gene, 35, pp: 201140, 2023.

[10] Shusen Zhou*, Qingcai Chen, and Xiaolong Wang. Fuzzy Deep Belief Networks for Semi-Supervised Sentiment Classification. Neurocomputing, 131(0), pp: 312-322, 2014. (SCI, IF: 2.005)

[11] Shusen Zhou*, Qingcai Chen, and Xiaolong Wang. Active Semi-Supervised Learning Method with Hybrid Deep Belief Networks. PLoS ONE, 9(9), pp: e107122, 2014. (SCI, IF: 3.534)

[12] Shusen Zhou*, Hailin Zou, Chanjuan Liu, Mujun Zang, Zhiwang Zhang, Jun Yue. Deep Extractive Networks for Supervised Learning. Optik, 127(20), pp:9008-9019, 2016. (SCI, IF:0.835)

[13] Shusen Zhou, Qingcai Chen*, and Xiaolong Wang. Handwritten Chinese Text Editing and Recognition System. Multimedia Tools and Applications (MTA), 71(3), pp: 1363-1380, 2012. (SCI, IF: 0.617)

[14] Shusen Zhou*, Qingcai Chen, and Xiaolong Wang. Convolutional Deep Networks for Visual Data Classification. Neural Processing Letters (NEPL), 38(1), pp: 17-27, 2013. (SCI, IF: 0.75)

[15] Shusen Zhou*, Qingcai Chen, and Xiaolong Wang. Active Deep Learning Method for Semi-Supervised Sentiment Classification. Neurocomputing, 120(0), pp: 536-546, 2013. (SCI, IF: 2.005)

[16] Shusen Zhou*, Qingcai Chen and Xiaolong Wang. Iterative Deep Networks for Semi-Supervised Image Classification. ICIC Express Letters, 9(7), pp: 1877-1883, 2015. (EI)

[17] Yan Liu, Shusen Zhou, and Qingcai Chen*. Discriminative Deep Belief Networks for Visual Data Classification. Pattern Recognition (PR), 44(10-11), pp: 2287-2296, 2011. (SCI: 12050666, IF: 2.607, EI: 20112514071848)

[18] Shusen Zhou*, Qingcai Chen and Xiaolong Wang. Deep Networks for Online Handwriting Chinese Character Recognition. ICIC Express Letters, 9(6), pp: 1783-1789, 2015. (EI)

[19] Xiaoling Li*, Shusen Zhou. Deep Learning Method for Incomplete Data Classification. Journal of Computational Information Systems, 11(20), pp:1-8, 2015. (EI)

[20] Shusen Zhou*, Qingcai Chen, Xiaolong Wang, et al. A Novel Algorithm for Online Handwriting Chinese Document Recognition. ICIC Express Letters, 5(11), pp: 4245-4250, 2011. (EI: 20114314458315)

[21] Shusen Zhou*, Qingcai Chen, and XiaolongWang, et al. Hybrid Deep Belief Networks for Semi-supervised Sentiment Classification. International Conference on Computational Linguistics (COLING), August 23-29, pp: 1341-1349, Dublin, Ireland, 2014. (EI)

[22] Shusen Zhou*, Qingcai Chen, Xiaolong Wang, et al. An Empirical Evaluation on Online Chinese Handwriting Databases. International Workshop on Document Analysis Systems (DAS), March 27-29, pp: 455-459, Gold Coast, QLD, Australia, 2012. (EI: 20122115054612)

[23] Shusen Zhou*, Qingcai Chen, Xiaolong Wang, et al. An Empirical Evaluation on HIT-OR3C Database. International Conference on Document Analysis and Recognition (ICDAR), September 18-21, pp: 1150-1154, Beijing, China, 2011. (EI: 20114814571145, ISTP: 12345352)

[24] Shusen Zhou*, Qingcai Chen, and Xiaolong Wang. Discriminate Deep Belief Networks for Image Classification. International Conference on Image Processing (ICIP), September 26-29, pp: 1561-1564, Hong Kong, China, 2010. (EI: 20110213574279)

[25] Shusen Zhou*, Qingcai Chen, and Xiaolong Wang. Deep Quantum Networks for Classification. International Conference on Pattern Recognition (ICPR), August 23-26, pp: 2885-2888, Istanbul, Turkey, 2010. (EI: 20104613390154, ISTP: 11578187)

[26] Shusen Zhou*, Qingcai Chen, and XiaolongWang. HIT-OR3C: An Opening Recognition Corpus for Chinese Characters. International Workshop on Document Analysis Systems (DAS), June 9-11, pp: 223-230, Boston, MA, USA, 2010. (EI: 20103113108286)

[27] Shusen Zhou*, Qingcai Chen, and XiaolongWang. Active Deep Networks for Semi-Supervised Sentiment Classification. International Conference on Computational Linguistics (COLING), August 23-27, pp: 1515-1523, Beijing, China, 2010. (EI: 20114014399497)

[28] Shusen Zhou*, Qingcai Chen, and XiaolongWang. Deep Adaptive Networks for Image Classification. International Conference on Internet Multimedia Computing and Service (ICIMCS), December 30-31, pp: 61-64, Harbin, China, 2010. (EI: 20111113748644)

[29] Shusen Zhou*, Qingcai Chen, Dandan Wang, et al. A Corpus-Based Concatenative Mandarin Singing Voice Synthesis System. International Conference on Machine Learning and Cybernetics (ICMLC), July 12-15, pp: 2695-2699, Kunming, China, 2008. (EI: 20085211817258, ISTP: BII01)

[30] Qingcai Chen*, Shusen Zhou, Dandan Wang, et al. Adaptive Filter Based Prosody Modification Approach. Conference of the International Speech Communication Association (INTERSPEECH), September 22-26, pp: 789-792, Brisbane, Australia, 2008. (EI: 20104813419404, ISTP: BOM81)