柴一栋  (研究员)

博士生导师 硕士生导师

办公地点：管理学院0908办公室

学位：博士学位

在职信息：在职

毕业院校：清华大学

   
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个人简介

        柴一栋，研究员，博士生导师。博士毕业于清华大学经管学院管理科学与工程系（信息系统方向），主要关注如何设计创新性的人工智能方法，更好地服务于个人、组织和社会的现代科学化管理，使用的机器学习方法包括深度学习、对抗学习、迁移学习、联邦学习、强化学习、贝叶斯学习等，具体的应用领域包括信息系统安全与网络空间管理、智慧医疗管理、商务智能管理等。以第一作者或通讯作者发表研究成果于MISQ、ISR、JMIS等管理信息系统顶刊（UTD/FT），IEEE TDSC、IEEE TPAMI、IEEE TKDE、ACM TOIS等信息安全/人工智能/数据挖掘等领域的顶刊（CCF A），以及《管理科学学报》等中文顶刊。发表学术专著一部，授权专利多项。获全国首届数据空间大会优秀科技成果奖、国际信息系统权威会议WITS 2021 best paper award、清华大学优秀博士论文等荣誉。担任ACM Transactions on AI Security and Privacy、《系统科学与系统工程学报》（英文版）、Industrial Management & Data Systems等期刊副主编，担任PACIS 2023 Design Science in IS Track联合主席，担任ICIS/PACIS副主编，担任MISQ、ISR、IEEE TDSC、POM、INFORMS JOC、JMIS等期刊审稿人。主持国家优秀青年基金等项目。

        指导的合工大博士生毕业后入职中科大（聘为特任副研究员）。指导学生以第一或通讯作者发表成果于ISR、INFORMS JOC、IEEE TDSC、IEEE TKDE、ACM TOIS、《管理科学学报》等顶刊10余篇，获“SWAIB（2025）最佳论文奖”“CNAIS（2024）推荐论文提名奖”、“第27届管理科学与工程国际会议暨博士生论坛优秀论文三等奖”、INFORMS Workshop on Data Science Best Paper Nominee等。

        


招生要求

专业不限。由于我的研究需要设计许多创新性人工智能方法，具有一定的难度，希望学生的求知欲强、数理功底好、编程能力强。优先考虑有科研理想的同学。


学术发表

管理学顶刊 (UTD/FT)

  1. A Novel Personalized Federated Learning Method for Privacy-Preserving Smart Mobile Health Monitoring. INFORMS Journal on Computing. 2026, 38(4),1165-1180. Coauthors: Haoxin Liu, Xiao Liu, Liuan Wang, Yi Liu, Junqiu Wang.

  2. Responsible AI-Enabled Infodemic Management: A Hypergraph-based Infodemic Topic Prediction Framework. INFORMS Journal on Computing. 2026, 38(4):1181-1197. Coauthors: Luyue Zhao, Shuai Ding, Jiaheng Xie, Xiao Fang, Shanlin Yang.

  3. Improving Competitiveness: A Freelancer-Centric Approach for Recommending Reskilling Strategies. Information Systems Research. Forthcoming. Coauthors: Haoxin Liu, Shuo Yu, Stephen He, Wen Wen.

  4. Short-Form Videos and Mental Health: A Knowledge-Guided Neural Topic Model. Information Systems Research. 2025, 37(1), 356-377. Coauthors: Jiaheng Xie, Ruicheng Liang, Yang Liu, ‪Daniel Dajun Zeng.

  5. RADAR: A Framework for Developing Adversarially Robust Cyber Defense AI Agents with Deep Reinforcement Learning. MIS Quarterly. 2025, 49(4), 1385–1416. Coauthors: Reza Ebrahimi, Weifeng Li, Jason Pacheco, and Hsinchun Chen.

  6. Motion Sensor-Based Fall Prevention for Senior Care: A Hidden Markov Model with Generative Adversarial Network Approach. Information Systems Research. 2024, 35(1). Coauthors: Shuo Yu, Sagar Samtani, Hongyan Liu, Hsinchun Chen

  7. Deep Learning for Information System Research. Journal of Management Information Systems, 2023, 40(1), 271–301. Coauthors: Sagar Samtani, Hongyi Zhu, Balaji Padmanabhan, Hsinchun Chen, Jay F Nunamker.

  8. Unbox the Black-box: Predict and Interpret YouTube Viewership Using Deep Learning. Journal of Management Information Systems, 2023, 40(2), 541-579. Coauthors: Jiaheng Xie, Xiao Liu.

  9. Cross-Lingual Cybersecurity Analytics in the International Dark Web with Adversarial Deep Representation Learning. MIS Quarterly, 2022, 46(2), 1209-1226. Coauthors: Reza Ebrahimi, Sagar Samtani, Hsinchun Chen.

  10. Wearable Sensor-based Chronic Condition Severity Assessment: An Adversarial Attention-based Deep Multisource Multitask Learning Approach. MIS Quarterly, 2022. 38(4), 1095-1121. Coauthors: Shuo Yu, Hsinchun Chen, Scott J. Sherman, Randall A. Brown.

  11. Linking Exploits from the Dark Web to Known Vulnerabilities for Proactive Cyber Threat Intelligence: An Attention-based Deep Structured Semantic Model. MIS Quarterly, 2022, 46(2), 911-946. Coauthors: Sagar Samtani, Hsinchun Chen

  12. Assessing and Enhancing Adversarial Robustness of Predictive Analytics: An Empirically Tested Design Framework. Journal of Management Information Systems, 2022, 39(2), 542-572. Coauthor: Weifeng Li

  13. Fall Detection with Wearable Sensors: A Hierarchical Attention-based Convolutional Neural Network Approach. Journal of Management Information Systems, 2021, 38(4), 1095-1121. Coauthors: Shuo Yu, Hsinchun Chen, Randall A. Brown, Scott J. Sherman, Jay F. Nunamaker, Jr.

 

人工智能/数据科学顶刊 (CCF-A)

  1. Balancing Imperceptible and Aggressive Poisoning Attack for Recommender Systems: A simple Multinomial Diffusion Model. ACM Transactions on Information Systems. 2026, 44(4), 1046-8188. Coauthors: Jun Zhu, Yuanchun Jiang, Yang Qian, Yang Wang.

  2. Emotion-aware Personalized Music Recommendation with a Heterogeneity-aware Deep Bayesian Network. ACM Transactions on Information Systems, 2025, 43(5), 1-43. Coauthors: Erkang Jing, Yezheng Liu, Shuo Yu, Longshun Liu, Yuanchun Jiang, Yang Wang.

  3. Additive Feature Attribution Explainable Methods to Craft Adversarial Attacks for Text Classification and Text Regression, IEEE Transactions on Knowledge and Data Engineering, 2023, 35(12), 12400–12414. Coauthors: Ruicheng Liang, Sagar, Samtani, Hongyi Zhu, Meng Wang, Yezheng Liu, Yuanchun Jiang.

  4. Heterogeneous Domain Adaptation with Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(2), 1862-1875. Coauthors: Reza Ebrahimi, Hao Zhang, Hsinchun Chen

  5. An Explainable Multi-Modal Hierarchical Attention Model for Developing Phishing Threat Intelligence. IEEE Transactions on Dependable and Secure Computing, 2022, 19(2), 790 – 803. Coauthors: Yonghang Zhou, Weifeng Li, Yuanchun Jiang.

 

其他发表

  1. Copyright Protection for Deep Regression Models: A Three-Stage Verification Method. Fundamental Research. 2026 March. Coauthors: Xinmei Wang, Yi Liu, Xiao Han, Yang Qian, Kun Yuan, Yezheng Liu.

  2. A Novel Modular Multistage Conversational Recommendation Method for High-Involvement Products. 管理科学学报. 2026, 6, 46-62. Coauthors: Yonghang Zhou, Yuanchun Jiang, Chunli Liu, Kun Yuan, Yezheng Liu.

  3. A reporting checklist for large language models in behavioural science. June 2026; Nature Human Behaviour. Coauthors: Feuerriegel, Stefan; Barrie, Christopher; Crockett, M. J. etc.

  4. Limited Preference Constrainted Personalized Demand Prediction Based on Text And Image Information.管理科学学报. 2025, 9, 52-64. Coauthor: Yuanchun Jiang, Yi Li, Yang Qian, Yezheng Liu.

  5. Graph Neural Network Recommendation System Adversarial Attack Method Based on Importance Maximization and Community Partition. 中国管理科学 . 2025, 33(2), 95-104. Coauthors: Haoxin Liu, Yuanchun Jiang, Yezheng Liu.

  6. Online Doctor Recommendation Considering the Uncertainty of Deep Learning Models. 中国管理科学 . 2025, 33(11), 151-161. Coauthors: Fulai Cui, Yuanchun Jiang, Yang Qian, Jianshan Sun, Yezheng Liu.

  7. A Bayesian Deep Recommender System for Uncertainty-Aware Online Physician Recommendation. Information and Management. 2024, 61(7), 104027. Coauthors: Fulai Cui, Shuo Yu, Yang Qian, Yuanchun Jiang, Yezheng Liu, Xiao Liu, Jianxin Li.

  8. A Profile Similarity-Based Personalized Federated Learning Method for Wearable Sensor-Based Human Activity Recognition. Information and Management. 2024, 61(7), 103922. Coauthors: Haoxin Liu, Hongyi Zhu, Yue Pan, Anqi Zhou, Hongyan Liu, Jianwei Liu, Yang Qian.

  9. Why Some Products Compete and Others Don’t: A Competitive Attribution Model from Customer Perspective. Decision Support Systems, 2023, 169 (June), 113956. Coauthors: Yang Qian, Yuanchun Jiang, Jennifer Shang, Yezheng Liu.

  10. A Deep Interpretable Representation Learning Method for Speech Emotion Recognition. Information Processing and Management. 2023, 60(6), 103501. Coauthors: Erkang Jing, Yezheng Liu, Jianshan Sun, Sagar Samtani, Yuanchun Jiang, Yang Qian.

  11.  Popularity Prediction for Marketer-Generated Content: A Text-Guided Attention Neural Network for Multi-Modal Feature Fusion. Information Processing & Management, 2022, 59(4), 102984. Coauthors: Yang Qian, Wang Xu, Xiao Liu, Haifeng Ling, Yuanchun Jiang, Yezheng Liu.

  12. Glaucoma Diagnosis in the Chinese Context: An Uncertainty Information-Centric Bayesian Deep Learning Model. Information Processing and Management. 2021, 58(2), 102454. Coauthors: Yiyang Bian, Hongyan Liu, Jiaxing Li, Jie Xu.