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Zhong (Carson) Chen
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Biography
I'm currently working as a tenure-track Assistant Professor (Data Science/Machine Learning) in the School of Computing, Southern Illinois University (SIU), Carbondale, Illinois. I'm also the Director of Learning, Optimization, and Analysis from Data Lab (LOAD Lab) at School of Computing, SIU. Previously, I was working as a Research Assistant Professor in Department of Radiation Oncology, University of Kansas Medical Center (KUMC), Kansas City, Kansas. Also, I was working as a Computational Scientist in the Department of Computer Science, Xavier University of Louisiana (XULA), New Orleans, Louisiana.
My current research interests include Data-centric AI, Large Language Models (LLMs) and Applications, (Interpretable and Trustworthy) Machine Learning, Deep Learning, Big Data Mining, Online Optimization, Outlier/Anomaly/Novelty Detection, Multi-omics Data Integration, Multi-modal Learning, Interpretable Time Series Forecasting using Environmental Data, and AI-related Applications. I have published more than 60 peer-reviewed articles in scientific journals and conferences such as PRL, IVC, JMLC, KAIS, TCBB, BioData Mining, Bioinformatics, Physica Medica, IEEE Access, IoT-J, T-ITS, T-IV, TKDE, MLJ, TNNLS, SDM'17'24'25, IEEE BigData'18'22'24, ACM-BCB'20, ICDM'22, CIKM'23, DSAA'23, IJCAI'25, AAAI'23'24'25, and NeurIPS'25. I have received the Excellence Reviewer Award of KDD'23, Outstanding Reviewer Award of KDD'25, the IJCAI'2025 Travel Award, and an IIN Seed Grant Award. I have served as a panelist at NSF. I have been invited to serve as the ad hoc reviewer of international journals including Cancer Research and Treatment (TCRT), Complexity, Information Sciences (INS), Neurocomputing, Cognitive Computation, IEEE Transactions on Medical Imaging (TMI), IEEE Transactions on Fuzzy Systems, ACM Transactions on Knowledge Discovery from Data (TKDD), Frontiers in Computational Neuroscience, Frontiers in Endocrinology, Frontiers in Oncology, Medical Physics, Physics in Medicine and Biology, Computers and Electrical Engineering (CEE), IEEE Transactions on Green Communications and Networking (TGCN), IEEE Internet of Things Journal (IoT), IEEE Transactions on Computational Social Systems (TCSS), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Transactions on Vehicular Technology (TVT), Computers and Electrical Engineering, International Journal of Machine Learning and Cybernetics (JMLC), Artificial Intelligence In Medicine (AIIM), Machine Learning with Applications (MLWA), Expert Systems with Applications (ESWA), Neural Networks, The Journal of Supercomputing, Information Processing and Management (IPM), ACM Transactions on Internet Technology (TOIT), Transactions on Knowledge and Data Engineering (TKDE), Electronics, Journal of Industrial Information Integration (JIII), Engineering Applications of Artificial Intelligence (EAAI), Journal of Advanced Transportation, and Briefings in Bioinformatics; reviewer and PC member of international conferences such as ICDM'16, SDM'17, ICDM'17, ICDM'18, AAAI'19, CIKM'19, ICDM'19, AAAI'20, ICDM'20, AAAI'21, ICDM'21, AAAI'22, IJCAI'22, ICDM'22, BIBM'22, AAAI'23, PAKDD'23, IJCAI'23, KDD'23, FAccT'23 (PC), SMC'23, AAAI'24 (PC), SDM'24, PAKDD'24, IJCAI'24 (PC), KDD'24, ECML-PKDD'24 (PC), ICPR'24, ECAI'24 (PC), AAAI'25 (PC), ICDM'24 (PC), AAAI-AISI'25 (PC), KDD'25 (PC), ICLR'25, PAKDD'25 (PC), SDM'25, IJCAI'25 (PC), ICME'25, ECML-PKDD'25 (PC), ACML'25, AVSS'25 (Meta-Reviewer/Area Chair), ICDM'25 (PC), CIKM'25 (PC), ECAI'25 (PC), ACM-BCB'25, KDD'26, AAAI-AISI'26 (PC), AAAI'26 (PC), PAKDD'26 (PC), AISTATS'26, ICLR'26, and WWW'26 (PC).
( * First Author; # Collaborative Author) An Oversampling-enhanced Multi-class Imbalanced Classification Framework for Patient Health Status Prediction Using Patient-reported Outcomes [PDF] A few-shot U-net learning framework for fast and accurate three-dimensional dose prediction in radiotherapy [PDF] SolverLLM: Leveraging Test-Time Scaling for Optimization Problem via LLM-Guided Search [PDF] 3D Multi-Object Tracking Based on Masked Auto Encoder and Deep Hashing Paradigm [PDF] Face4FairShifts: A Large Image Benchmark for Fairness and Robust Learning across Visual Domains [PDF] Decoding Ancestry-Specific Genetic Risk: Interpretable Deep Feature Selection Reveals Prostate Cancer SNP Disparities in Diverse Populations [PDF] A Hybrid Ensemble End-to-end Neural Network for Accurate Protein-Protein Interactions Prediction [PDF] Online outlier detection in open feature spaces [PDF] Short- and Long-term Weekly Patient-reported Outcomes Prediction Undergoing Radiotherapy: Single-patient Time Series Model vs. Transformers-based Multi-patient Time Series Model [PDF] An Efficient Federated Learning Framework for Enhancing Data Diversity and Communication in Industrial IoT Fault Diagnosis [PDF] Advanced Anomaly Detection Framework for Enhancing Prediction of Severe Health Outcomes in Cancer Patients Undergoing Radiotherapy [PDF] A Novel Sparse Active Online Learning Framework for Fast and Accurate Streaming Anomaly Detection over Data Streams [PDF] Distributed Collaborative Learning with Representative Knowledge Sharing [PDF] Measuring Heterogeneity in Machine Learning with Distributed Energy Distance [PDF] MCCA-MOT: Multimodal collaboration-guided cascade association network for 3D multi-object tracking [PDF] $\ell_{1,\infty}$-Mixed Norm Promoted Row Sparsity for Fast Online CUR Decomposition Learning in Varying Feature Spaces [PDF] Metric-Agnostic Continual Learning for Sustainable Group Fairness [PDF] Balancing Cost and Completion Time Through Variable Paths with Variable Bandwidth in HPNs [PDF] An Oversampling-enhanced Multi-class Imbalanced Classification Framework for Patient Health Status Prediction Using Patient-reported Outcomes [PDF] Accounting for Cancer Patients with Severe Outcomes: An Anomaly Detection Perspective [PDF] A Dynamic 3D Multi-Object Tracking Method Based on Spatiotemporal Features [PDF] Optimal Scheduling Algorithms for Cost-Effective Bandwidth Reservation in HPNs [PDF] $\ell_{1,2}$-Norm and CUR Decomposition based Sparse Active Online Learning for Data Streams with Streaming Features [PDF] An end-to-end knowledge graph fused graph neural network for accurate protein-protein interactions prediction [PDF] Accurate proton-photon patient selection via dose and NTCP prediction for head-and-neck patients [PDF] Adaptive Sparse Online Learning through Asymmetric Truncated Gradient [PDF] $\ell_{1,2}$-Norm and CUR Matrix Decomposition based Sparse Active Online Learning for Data Streams with Streaming Features [PDF] Advancing Graph Counterfactual Fairness through Fair Disentangled Representation [PDF] Individual Fairness with Group Awareness under Uncertainty [PDF] Robust Sparse Online Learning through Adversarial Sparsity Constraints [PDF] Robust Sparse Online Learning for Data Streams with Streaming Features [PDF] MKG-FENN: A Multimodal Knowledge Graph Fused End-to-End Neural Network for Accurate Drug–Drug Interaction Prediction [PDF] Defense Against Adversarial Attacks for Neural Representations of Text [PDF] Cost-sensitive Sparse Group Online Learning for Imbalanced Data Streams [PDF] Simplex2vec Backward: From Vectors Back to Simplicial Complex [PDF] Defending the Graph Reconstruction Attacks for Simplicial Neural Networks [PDF] MMA: Multi-Metric-Autoencoder for Analyzing High-Dimensional and Incomplete Data [PDF] Quitting Smoking after a Cancer Diagnosis is associated with High-Risk Neutrophil-to-Lymphocyte Ratio among Tobacco Use-Related Cancer Survivors [PDF] Online Semi-supervised Learning with Mix-Typed Streaming Features [PDF] An Effective Cost-sensitive Sparse Online Learning Framework for Imbalanced Streaming Data Classification and Its Application to Online Anomaly Detection [PDF] Proximal Cost-sensitive Sparse Group Online Learning [PDF] Projection Dual Averaging based Second-order Online Learning [PDF] Driver Gene Detection through Bayesian Network Integration of Mutation and Expression Profiles [PDF] Effective Cancer Subtype and Stage Prediction via Dropfeature-DNNs [PDF] Insufficient Lycopene Intake is Associated with High Risk of Prostate Cancer: A Cross-Sectional Study from the National Health and Nutrition Examination Survey (2003-2010) [PDF] CSRDA: Cost-sensitive Regularized Dual Averaging for Handling Imbalanced and High-dimensional Streaming Data [PDF] A Deep Imputation and Inference Framework for Estimating Personalized and Race-specific Causal Effects of Genomic Alterations on PSA [PDF] Seeking The Exclusive Binding Region of Phenylalkylamine Derivatives on Human T-type Calcium Channels via Homology Modeling and Molecular Dynamics Simulation Approach [PDF] Adaptive Robust Local Online Density Estimation for Streaming Data [PDF] Fusion Lasso and Its Applications to Cancer Subtype and Stage Prediction [PDF] Inferring Personalized and Race-specific Causal Effects of Genomic Aberrations on Gleason Scores: A Deep Latent Variable Model [PDF] Learning Discriminative Subregions and Pattern Orders for Facial Gender Classification [PDF] Online Density Estimation over Streaming Data: A Local Adaptive Solution [PDF] CSTG: An Effective Framework for Cost-sensitive Sparse Online Learning [PDF] Construction Method of Concept Lattice Based on Improved Variable Precision Rough Set [PDF] An Ontology-based Approach for Measuring Semantic Similarity Between Words [PDF] Personalized Route Planning System Based on Wardrop Equilibrium Model for Campus Evacuation [PDF] An Improved Saliency Detection Approach for Flying Apsaras in the Dunhuang Grotto Murals, China [PDF] Topologically Ordered Feature Extraction Based on Sparse Group Restricted Boltzmann Machines [PDF] A Kernel Support Vector Machine-based Feature Selection Approach for Recognizing Flying Apsaras' Streamers in the Dunhuang Grotto Murals, China [PDF] Subspace Clustering Mutation Operator for Developing Convergent Differential Evolution Algorithm [PDF] Multiobjective Optimization of Evacuation Routes in Stadium Using Superposed Potential Field Network Based ACO [PDF] Workshop Proposal Co-authors & Tentative Program Committee Teaching in Computer Science at SIU Service of Computer Science Committee at SIU
Updated September 2025
2025
Yang Yan, Zhong Chen#, Cai Xu, Xinglei Shen, Jay Shiao, John Einck, Ronald C Chen, and Hao Gao
IEEE Access, 2025.
Zhong Chen*, Wangyao Li, Xinglei Shen, Ronald Chen, Yuting Lin, and Hao Gao
European Journal of Medical Physics (Physica Medica), 2025.
Dong Li, Xujiang Zhao, Linlin Yu, Yanchi Liu, Wei Cheng, Zhengzhang Chen, Zhong Chen#, Feng Chen, Chen Zhao, and Haifeng Chen
The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS'25), San Diego, CA, 2025. (Acceptance Rate 5,290/21,575=24.52%)
Saiyu Li, Zhong Chen#, Hui Li, Ye Tao, Ying Gao, and Jun Yan
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2025.
Yumeng Lin, Dong Li, Xintao Wu, Minglai Shao, Xujiang Zhao, Zhong Chen#, and Chen Zhao
arXiv preprint arXiv:2509.00658, 2025.
Zhong Chen*, Zichen Lao, You Lu, Wensheng Zhang, Andrea Edwards, and Kun Zhang
BioData Mining, 2025.
Jie Yang, Xijie Lan, Guoyin Wang, Zhong Chen#, Yuwen Chen, and Di Wu
IEEE Transactions on Computational Biology and Bioinformatics (TCBB), 2025.
Heng Lian, Yi He, Di Wu, Zhong Chen#, Xingquan Zhu, and Xindong Wu
IEEE Transactions on Knowledge and Data Engineering (TKDE), 37(10), pp. 6091-6106, 2025.
Yang Yan, Zhong Chen#, Xinglei Shen, Ronald C Chen, and Hao Gao
BioData Mining, 18(1), p.53, 2025.
Xuehua Sun, Zengsen Yuan, Xiangguang Kong, Liang Xue, Han Cheng, and Zhong Chen#
IEEE Internet of Things Journal (IoT-J), 12(7), pp. 36562-36576, 2025.
Yang Yan, Christopher Lominska, Gregory N Gan, Hao Gao, and Zhong Chen#
IEEE International Conference on Big Data Computing Service and Machine Learning Applications (BigDataService'25), pp. 73-80, 2025.
Zhong Chen*, Yi He, Di Wu, Chen Zhao, and Meikang Qiu
Proceedings of the 34th International Joint Conference on Artificial Intelligence (IJCAI'25), pp. 2740-2748, 2025. (Regular Paper, Acceptance Rate 1,023/5,806=17.62%)
Joseph Casey, Qianjiao Chen, Mengchen Fan, Baocheng Geng, Roman Shterenberg, Zhong Chen#, and Keren Li
Mathematics, 13(6): 1004, 2025.
Mengchen Fan, Baocheng Geng, Roman Shterenberg, Joseph A. Casey, Zhong Chen#, and Keren Li
arXiv preprint arXiv: 2501.16174, 2025.
Hui Li, Hengyuan Liu, Zhenzhen Du, Zhong Chen#, and Ye Tao
IEEE Transactions on Intelligent Transportation Systems (T-ITS), 26(1), pp. 974-989, 2025.
Zhong Chen*, Yi He, Di Wu, Wenbin Zhang, and Zhiqiang Deng
Proceedings of the 2025 SIAM International Conference on Data Mining (SDM'25), Alexandria, Virginia, 2025. (Regular Paper, Acceptance Rate 61/228=26.7%)
Heng Lian, Chen Zhao, Zhong Chen#, Xingquan Zhu, My T. Thai, and Yi He
The 39th AAAI Conference on Artificial Intelligence (AAAI'25), Philadelphia, PA, 2025. (Regular Paper, Acceptance Rate 3,032/12,957=23.4%)
Liudong Zuo, Zhong Chen#, and Lai Pan
International Conference on Computing, Networking and Communications (ICNC'25), pp. 113-117, 2025.
2024
Yang Yan, Zhong Chen#, Cai Xu, Xinglei Shen, Jay Shiao, John Einck, Ronald C Chen, and Hao Gao
arXiv preprint arXiv:2411.10819, 2024.
Yang Yan, Christopher Lominska, Gregory N Gan, Hao Gao, and Zhong Chen#
IEEE International Conference on Big Data (IEEE BigData'24), pp. 8225-8227, 2024.
Hui Li, Haoran Yang, Xiaoxue Ai, Zhong Chen#, and Yanli Wu
IEEE Transactions on Intelligent Vehicles (T-IV), 2024.
Liudong Zuo, Lai Pan, and Zhong Chen#
IEEE International Conference on Big Data (IEEE BigData'24), pp. 483-488, 2024. (Short Paper, Acceptance Rate 130/660=19.7%)
Zhong Chen*, Yi He, Di Wu, Liudong Zuo, Keren Li, Wenbin Zhang, and Zhiqiang Deng
IEEE International Conference on Big Data (IEEE BigData'24), pp. 374-383, 2024. (Regular Paper, Acceptance Rate 124/660=18.8%)
Jie Yang, Yapeng Li, Guoyin Wang, Zhong Chen#, and Di Wu
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 21(6), pp. 2518-2530, 2024.
Jiaxin Li, Zhong Chen#, Fazal Khan, Yanan Zhu, Gregory N Gan, Christoper Lominska, Qiang Li, Weiqiang Chen, Hao Gao, and Yuting Lin
International Journal of Particle Therapy (IJPT), 12, p.100145, 2024.
Zhong Chen*
The 10th IEEE International Conference on Big Data Computing Service and Machine Learning Applications (IEEE BigDataService 2024), pp. 44-51, 2024. (Regular Paper, Accepted)
Zhong Chen*
The 1st International Conference on Artificial Intelligence & Machine Learning (AIM'24), San Francisco, CA, 2024. (Oral Presentation)
Zichong Wang, Zhibo Chu, Ronald Blanco, Zhong Chen#, Shu-Ching Chen, and Wenbin Zhang
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'24), pp. 40-58, 2024. (Regular Paper, Acceptance Rate 198/826=24.0%)
Zichong Wang, Xiaoyong Yuan, Zhong Chen#, Yanzhao Wu, Xin Yao, and Wenbin Zhang
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'24), pp. 89-106, 2024. (Regular Paper, Acceptance Rate 198/826=24.0%)
Zhong Chen*
The 9th IEEE International Conference on Smart Cloud (IEEE SmartCloud 2024), pp. 42-47, 2024. (Regular Paper, Accepted)
Zhong Chen*, Yi He, Di Wu, Huixin Zhan, Victor Sheng, and Kun Zhang
Proceedings of the 2024 SIAM International Conference on Data Mining (SDM'24), Houston, United States, pp. 181-189, 2024. (Regular Paper, Acceptance Rate 98/416=23.6%)
Di Wu, Wu Sun, Yi He, Zhong Chen#, and Xin Luo
The 38th AAAI Conference on Artificial Intelligence (AAAI'24), Vancouver, Canada, 38(9), pp. 10216-10224, 2024. (Regular Paper, Acceptance Rate 2342/9862=23.75%)
Huixin Zhan, Kun Zhang, Zhong Chen#, and Victor Sheng
Hawaii International Conference on System Sciences 2024 (HICSS'24), pp. 7592-7601, 2024.
Zhong Chen*, Victor Sheng, Andrea Edwards, and Kun Zhang
Machine Learning (MLJ), 113, pp. 4407-4444, 2024.
2023
Huixin Zhan, Kun Zhang, Zhong Chen#, and Victor Sheng
The 32nd ACM International Conference on Information and Knowledge Management (CIKM'23), Birmingham, United Kingdom, 2023. (Short Paper, Acceptance Rate 152/554=27.4%)
Huixin Zhan, Kun Zhang, Zhong Chen#, and Victor Sheng
The 10th IEEE International Conference on Data Science and Advanced Analytics (DSAA'23), Thessaloniki, Greece, 2023. (Special Session Paper, Acceptance Rate 12/35=34.3%)
Cheng Liang, Di Wu, Yi He, Zhong Chen#, Teng Huang, and Xin Luo
The 22ed European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'23), Turin, Italy, 2023. (Regular Paper, Acceptance Rate 199/830=24.0%)
You Lu, Katherine Kwong, James Wells, Andrea Edwards, Zhong Chen#, Tung-Sung Tseng, and Kun Zhang
Scientific Reports, 13(1), p.2745, 2023.
Di Wu, Shengda Zhuo, Yu Wang, Zhong Chen#, and Yi He
The 37th AAAI Conference on Artificial Intelligence (AAAI'23), Washington DC, United States, 2023. (Regular Paper, Acceptance Rate 1721/8777=19.6%)
Zhong Chen*, Victor Sheng, Andrea Edwards, and Kun Zhang
Knowledge and Information Systems (KAIS), 65(1), pp. 59–87, 2023.
2022
Zhong Chen*, Huixin Zhan, Victor Sheng, Andrea Edwards, and Kun Zhang
The 2022 IEEE International Conference on Big Data (IEEE Big Data'22), pp. 495-504, Osaka, Japan, 2022. (Regular Paper, Acceptance Rate 122/633=19.3%)
Zhong Chen*, Huixin Zhan, Victor Sheng, Andrea Edwards, and Kun Zhang
The 22nd IEEE International Conference on Data Mining (ICDM'22), pp. 51-60, Orlando, Florida, United States, 2022. (Regular Paper, Acceptance Rate 85/885=9.6%)
Zhong Chen*, You Lu, Bo Cao, Wensheng Zhang, Andrea Edwards, and Kun Zhang
Bioinformatics, 38(10), pp. 2781–2790, 2022.
Zhong Chen*, Wensheng Zhang, Hongwen Deng, and Kun Zhang
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 19(1), pp. 107-120, 2022.
2021
You Lu, Andrea Edwards, Zhong Chen#, Tung-sung Tseng, Mirandy Li, Gabrielle V Gonzalez, and Kun Zhang
Frontiers in Public Health (FPH), p.792572, 2021.
Zhong Chen*, Zhide Fang, Victor Sheng, Andrea Edwards, and Kun Zhang
The 12th IEEE International Conference on Big Knowledge (ICBK'21), pp. 164-173, Auckland, New Zealand, 2021. (Regular Paper)
Zhong Chen*, Bo Cao, Andrea Edwards, Hongwen Deng, and Kun Zhang
Journal of Bioinformatics and Computational Biology (JBCB), 19(4), p.2150016, 2021.
You Lu, Ming Li, Gi Young Lee, Na Zhao, Zhong Chen#, Andrea Edwards, and Kun Zhang
Pharmacology Research & Perspectives (PRP), 9(3), p.e00783, 2021.
Zhong Chen*, Zhide Fang, Victor S Sheng, Jiabin Zhao, Wei Fan, Andrea Edwards, and Kun Zhang
International Journal of Machine Learning and Cybernetics (JMLC), 12(6), pp. 1803-1824, 2021.
2020
Zhong Chen*, Andrea Edwards, and Kun Zhang
The 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB'20), Virtual, pp. 1-8, 2020. (Short Paper, Acceptance Rate 17/130=13.1%)
Zhong Chen*, Andrea Edwards, Chindo Hicks, and Kun Zhang
Frontiers in Oncology (FIO), 10, pp. 272, 2020.
2019
Zhong Chen*, Andrea Edwards, Yongsheng Gao, and Kun Zhang
Image and Vision Computing (IVC), 89, pp. 144-157, 2019.
2018
Zhong Chen*, Zhide Fang, Jiabin Zhao, Wei Fan, Andrea Edwards, and Kun Zhang
2018 IEEE International Conference on Big Data (BigData'18), pp. 201-210, Seattle, Washington, United States, 2018. (Regular Paper, Acceptance Rate 98/518=19.7%)
2017
Zhong Chen*, Zhide Fang, Wei Fan, Andrea Edwards, and Kun Zhang
The 2017 SIAM International Conference on Data Mining (SDM'17), pp. 759-767, Houston, Texas, United States, 2017. (Regular Paper, Acceptance Rate 93/358=26.0%)
2016
Ruiling Zhang, Shengwu Xiong, and Zhong Chen#
Neurocomputing (NC), 188, pp. 326-338, 2016.
2015
Ruiling Zhang, Shengwu Xiong, and Zhong Chen#
International Conference on Intelligent Computing (ICIC'15), 9227, pp. 510-516, 2015.
Pengfei Duan, Haohao Zhang, Shengwu Xiong, Siqin Zhou, Zhong Chen#, and Pengcheng Yang
The 2nd International Symposium on Dependable Computing and Internet of Things (DCIT'15), 2015.
Zhong Chen*, Shengwu Xiong, Qingzhou Mao, Zhixiang Fang, and Xiaohan Yu
Advances in Multimedia (AIM), 2015.
Zhong Chen*, Shengwu Xiong, Zhixiang Fang, Ruiling Zhang, Xiangzhen Kong, and Yi Rong
Mathematical Problems in Engineering (MPIE), 2015.
2014
Zhong Chen*, Shengwu Xiong, Zhixiang Fang, Qingquan Li, Baolin Wang, and Qin Zou
Pattern Recognition Letters (PRL), 49, pp. 107-113, 2014.
Zhongbo Hu, Shengwu Xiong, Xiuhua Wang, Qinghua Su, Mianfang Liu, and Zhong Chen#
Mathematical Problems in Engineering (MPIE), 2014.
2013
Jialiang Kou, Shengwu Xiong, Zhixiang Fang, Xinlu Zong, and Zhong Chen#
Computational Intelligence and Neuroscience (CIN), 2013.