Zhong Chen

Zhong Chen
Assistant Professor in Data Science and Machine Learning
School of Computing, Southern Illinois University (SIU), Carbondale, IL, United States

Office: Engineering Building
Address: 1230 Lincoln Dr, Carbondale, IL 62901 (MAIL CODE 4511)
Southern Illinois University (SIU), Carbondale, IL, United States

Emails: zhong.chen AT cs DOT siu DOT edu (or zchen2 AT kumc DOT edu or zchen AT xula DOT edu) 
Homepage: https://pursuerchen.github.io/homepage
Dirtector of LOAD Lab: Learning, Optimization, and Analysis from Data Lab (LOAD Lab)
School of Computing at SIU: https://soc.siu.edu/ 
SIU department website: https://cs.siu.edu/faculty-staff/continuing_faculty.php

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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, Carbondale, IL 62901, United States. 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 (KC), KS 66160, United States. Also, I was working as a Computational Scientist in the Department of Computer Science, Xavier University of Louisiana, New Orleans, LA 70125, United States.

My primary research interests are in the fields of medical physics, big data mining, machine learning, deep learning, and bioinformatics. My research focuses on the development, analysis, implementation, and experimental evaluation of big streaming data mining algorithms, machine learning and deep learning techniques, and applications in healthcare and medical physics. I am an Associate Editor at the Editorial Board of Medical Physics and an Editorial Member of Computational Biology and Bioinformatics. I am a Review Editor on the Editorial Board of Frontiers in Neurorobotics and Frontiers in Big Data and I have served as one of Program Committees at the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'23), 2023 ACM Conference on Fairness, Accountability, and Transparency (FAccT'23), the 38th Annual AAAI Conference on Artificial Intelligence (AAAI'24), the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD'24), the Second IEEE International Conference on Medical Artificial Intelligence (MedAI'24), the 9th IEEE International Conference on Smart Cloud (IEEE SmartCloud'24), the 10th IEEE International Conference on Big Data Security on Cloud (BigDataSecurity'24), the 17th International Conference on Knowledge Science, Engineering and Management (KSEM'24), the 27th European Conference on Artificial Intelligence (ECAI'24), the 39th Annual AAAI Conference on Artificial Intelligence (AAAI'25), and IEEE International Conference on Data Mining (ICDM'24), AAAI 2025 Artificial Intelligence for Social Impact Track (AAAI-AISI'25), and the 31st SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'25). In addition, I have been invited to serve as the ad hoc reviewer of international journals including Technology in 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, 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), Expert Systems with Applications (ESWA), and Briefings in Bioinformatics; and international conferences such as ICDM'16, SDM'17, ICDM'17, ICDM'18, AIKE'18, ICAIS'19, 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, SMC'23, AAAI'24, SDM'24, PAKDD'24, IJCAI'24, KDD'24, ECML PKDD'24, IEEE SmartCloud'24, BigDataSecurity'24, KSEM'24, ICPR'24, ECAI'24, AAAI'25, ICDM'24, AAAI-AISI'25, KDD'25, ICLR'25, PAKDD'25, and SDM'25.

My co-authors include Prof. Kun Zhang (XULA), Prof. Victor Sheng (TTU), Prof. Zhide Fang (LSUHSC), Prof. Yi He (ODU), Prof. Wenbin Zhang (FIU), Prof. Di Wu (SWU), Dr. Huixin Zhan (TTU), Prof. Hongwen Deng (TU), Prof. Chindo Hicks (LSUHSC), Prof. Yongsheng Gao (GU), Prof. Zhixiang Fang (WU), Prof. Qin Zou (WU), and etc.

Employment History

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What's New

Publications

( * First  Author;  # Collaborative  Author)


    2024

  1. Adaptive Sparse Online Learning through Asymmetric Truncated Gradient [PDF]
    Zhong Chen*
    The 10th IEEE International Conference on Big Data Computing Service and Machine Learning Applications (IEEE BigDataService 2024), 2024. (Regular Paper, Accepted)

  2. Advancing Graph Counterfactual Fairness through Fair Disentangled Representation [PDF]
    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), Vilnius, 2024. (Regular Paper, Accepted)

  3. Individual Fairness with Group Awareness under Uncertainty [PDF]
    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), Vilnius, 2024. (Regular Paper, Accepted)

  4. Robust Sparse Online Learning through Adversarial Sparsity Constraints [PDF]
    Zhong Chen*
    The 9th IEEE International Conference on Smart Cloud (IEEE SmartCloud 2024), New York City, United States, 2024. (Regular Paper, Accepted)

  5. Robust Sparse Online Learning for Data Streams with Streaming Features [PDF]
    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, Accepted)

  6. MKG-FENN: A Multimodal Knowledge Graph Fused End-to-End Neural Network for Accurate Drug–Drug Interaction Prediction [PDF]
    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%, Accepted)

  7. Defense Against Adversarial Attacks for Neural Representations of Text [PDF]
    Huixin Zhan, Kun Zhang, Zhong Chen#, and Victor Sheng
    Hawaii International Conference on System Sciences 2024 (HICSS'24), pp. 7592-7601, 2024. (Accepted)


    8. 2023

  8. Cost-sensitive Sparse Group Online Learning for Imbalanced Data Streams [PDF]
    Zhong Chen*, Victor Sheng, Andrea Edwards, and Kun Zhang
    Machine Learning (MLJ), 2023. (Accepted)

  9. Simplex2vec Backward: From Vectors Back to Simplicial Complex [PDF]
    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%, Accepted)

  10. Defending the Graph Reconstruction Attacks for Simplicial Neural Networks [PDF]
    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%, Accepted)

  11. MMA: Multi-Metric-Autoencoder for Analyzing High-Dimensional and Incomplete Data [PDF]
    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%)

  12. Quitting Smoking after a Cancer Diagnosis is associated with High-Risk Neutrophil-to-Lymphocyte Ratio among Tobacco Use-Related Cancer Survivors [PDF]
    You Lu, Katherine Kwong, James Wells, Andrea Edwards, Zhong Chen#, Tung-Sung Tseng, and Kun Zhang
    Scientific Reports, 13(1), p.2745, 2023. 

  13. Online Learning in Mixed Data Feature Spaces under Semi-supervision [PDF]
    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%)

  14. An Effective Cost-sensitive Sparse Online Learning Framework for Imbalanced Streaming Data Classification and Its Application to Online Anomaly Detection [PDF]
    Zhong Chen*, Victor Sheng, Andrea Edwards, and Kun Zhang
    Knowledge and Information Systems (KAIS), 65(1), pp. 59–87, 2023. 


    15. 2022

  15. Proximal Cost-sensitive Sparse Group Online Learning [PDF]
    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%)

  16. Projection Dual Averaging based Second-order Online Learning [PDF]
    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%)

  17. Driver Gene Detection through Bayesian Network Integration of Mutation and Expression Profiles [PDF]
    Zhong Chen*, You Lu, Bo Cao, Wensheng Zhang, Andrea Edwards, and Kun Zhang
    Bioinformatics, 38(10), pp. 2781–2790, 2022. 

  18. Effective Cancer Subtype and Stage Prediction via Dropfeature-DNNs [PDF]
    Zhong Chen*, Wensheng Zhang, Hongwen Deng, and Kun Zhang
    IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 19(1), pp. 107-120, 2022. 


    19. 2021

  19. 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]
    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. 

  20. CSRDA: Cost-sensitive Regularized Dual Averaging for Handling Imbalanced and High-dimensional Streaming Data [PDF]
    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)

  21. A Deep Imputation and Inference Framework for Estimating Personalized and Race-specific Causal Effects of Genomic Alterations on PSA [PDF]
    Zhong Chen*, Bo Cao, Andrea Edwards, Hongwen Deng, and Kun Zhang
    Journal of Bioinformatics and Computational Biology (JBCB), 19(4), p.2150016, 2021. 

  22. Seeking The Exclusive Binding Region of Phenylalkylamine Derivatives on Human T-type Calcium Channels via Homology Modeling and Molecular Dynamics Simulation Approach [PDF]
    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. 

  23. Adaptive Robust Local Online Density Estimation for Streaming Data [PDF]
    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. 


    24. 2020

  24. Fusion Lasso and Its Applications to Cancer Subtype and Stage Prediction [PDF]
    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%)

  25. Inferring Personalized and Race-specific Causal Effects of Genomic Aberrations on Gleason Scores: A Deep Latent Variable Model [PDF]
    Zhong Chen*, Andrea Edwards, Chindo Hicks, and Kun Zhang
    Frontiers in Oncology (FIO), 10, pp. 272, 2020. 


    26. 2019

  26. Learning Discriminative Subregions and Pattern Orders for Facial Gender Classification [PDF]
    Zhong Chen*, Andrea Edwards, Yongsheng Gao, and Kun Zhang
    Image and Vision Computing (IVC), 89, pp. 144-157, 2019. 


    27. 2018

  27. Online Density Estimation over Streaming Data: A Local Adaptive Solution [PDF]
    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%)


    28. 2017

  28. CSTG: An Effective Framework for Cost-sensitive Sparse Online Learning [PDF]
    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%)


    29. 2016

  29. Construction Method of Concept Lattice Based on Improved Variable Precision Rough Set [PDF]
    Ruiling Zhang, Shengwu Xiong, and Zhong Chen#
    Neurocomputing (NC), 188, pp. 326-338, 2016. 


    30. 2015

  30. An Ontology-based Approach for Measuring Semantic Similarity Between Words [PDF]
    Ruiling Zhang, Shengwu Xiong, and Zhong Chen#
    International Conference on Intelligent Computing (ICIC'15), 9227, pp. 510-516, 2015. 

  31. Personalized Route Planning System Based on Wardrop Equilibrium Model for Campus Evacuation [PDF]
    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. 

  32. An Improved Saliency Detection Approach for Flying Apsaras in the Dunhuang Grotto Murals, China [PDF]
    Zhong Chen*, Shengwu Xiong, Qingzhou Mao, Zhixiang Fang, and Xiaohan Yu
    Advances in Multimedia (AIM), 2015. 

  33. Topologically Ordered Feature Extraction Based on Sparse Group Restricted Boltzmann Machines [PDF]
    Zhong Chen*, Shengwu Xiong, Zhixiang Fang, Ruiling Zhang, Xiangzhen Kong, and Yi Rong
    Mathematical Problems in Engineering (MPIE), 2015. 


    34. 2014

  34. A Kernel Support Vector Machine-based Feature Selection Approach for Recognizing Flying Apsaras’ Streamers in the Dunhuang Grotto Murals, China [PDF]
    Zhong Chen*, Shengwu Xiong, Zhixiang Fang, Qingquan Li, Baolin Wang, and Qin Zou
    Pattern Recognition Letters (PRL), 49, pp. 107-113, 2014. 

  35. Subspace Clustering Mutation Operator for Developing Convergent Differential Evolution Algorithm [PDF]
    Zhongbo Hu, Shengwu Xiong, Xiuhua Wang, Qinghua Su, Mianfang Liu, and Zhong Chen#
    Mathematical Problems in Engineering (MPIE), 2014. 


    36. 2013

  36. Multiobjective Optimization of Evacuation Routes in Stadium Using Superposed Potential Field Network Based ACO [PDF]
    Jialiang Kou, Shengwu Xiong, Zhixiang Fang, Xinlu Zong, and Zhong Chen#
    Computational Intelligence and Neuroscience (CIN), 2013. 

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Teaching in Computer Science at SIU

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Updated October 2024

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