Address
6-266, Lau Ming Wai Academic Building, City University of Hong Kong
Phone
+852 34427492
Fax
+852 34420369
Email
Qualifications
PhD - Information Systems (Tsinghua University)
BSc - Information Systems (Beijing Institute of Technology)
Biography
Dr. Yidong Chai is an Associate Professor in the Department of Information Systems at the College of Business, City University of Hong Kong. His research focuses on designing innovative AI methods to support modern scientific management for individuals, organizations, and society. He employs a wide range of machine learning techniques, including large language models (LLMs), deep learning, Bayesian learning, adversarial learning, transfer learning, and federated learning. His application areas span smart healthcare management, information systems security and cyberspace governance, business intelligence, and fintech.
Dr. Chai has published in top-tier management science journals such as MISQ, ISR, JMIS, and INFORMS JOC (UTD/FT-listed), as well as top-tier computer science and AI journals such as IEEE TDSC, IEEE TPAMI, IEEE TKDE, and ACM TOIS (CCF A-listed). He has also published in top-tier Chinese journals such as管理科学学报. He has authored one academic monograph and holds dozens of authorized patents. He currently serves as an Associate Editor for ACM Transactions on AI Security and Privacy, Journal of Systems Science and Systems Engineering, and Industrial Management & Data Systems. He has led major research projects, including the National Excellent Young Scientists Fund.
Dr. Chai also supervises doctoral students at Hefei University of Technology (HFUT). One of his HFUT PhD students has joined the University of Science and Technology of China as an Assistant Professor. Under his mentorship, HFUT students have published first- or corresponding-author papers in top journals such as ISR, INFORMS JOC, IEEE TDSC, ACM TOIS, and 管理科学学报.
Publications
Journal Publications and Reviews
Xu, Jie; Jing, Erkang; Chai, Yidong / A deep learning model integrating domain-specific features for enhanced glaucoma diagnosis. December 2025; In: BMC Medical Informatics and Decision Making. Vol. 25, No. 1
Ebrahimi, Reza; Chai, Yidong; Li, Weifeng; Pacheco, Jason; Chen, Hsinchun / RADAR: A Framework for Developing Adversarially Robust Cyber Defense AI Agents with Deep Reinforcement Learning. December 2025; In: MIS Quarterly. Vol. 49, No. 4, pp. 1385-1416
Zhao, Luyue; Ding, Shuai; Chai, Yidong; Xie, Jiaheng; Fang, Xiao; Yang, Shanlin / Responsible AI-Enabled Infodemic Management: A Hypergraph-Based Infodemic Topic Prediction Framework. September 2025; In: INFORMS Journal on Computing.
JING, ERKANG; LIU, YEZHENG; CHAI, YIDONG; YU, SHUO; LIU, LONGSHUN; JIANG, YUANCHUN; WANG, YANG / Emotion-aware Personalized Music Recommendation with a Heterogeneity-aware Deep Bayesian Network. July 2025; In: ACM Transactions on Information Systems. Vol. 43, No. 5
Xie, Jiaheng; Chai, Yidong; Liang, Ruicheng; Liu, Yang; Zeng, Daniel Dajun / Short-Form Videos and Mental Health: A Knowledge-Guided Neural Topic Model. June 2025; In: Information Systems Research.
Cui, Fulai; Yu, Shuo; Chai, Yidong; Qian, Yang; Jiang, Yuanchun; Liu, Yezheng; Liu, Xiao; Li, Jianxin / A Bayesian deep recommender system for uncertainty-aware online physician recommendation. November 2024; In: Information & Management. Vol. 61, No. 7
Chai, Yidong; Liu, Haoxin; Zhu, Hongyi; Pan, Yue; Zhou, Anqi; Liu, Hongyan; Liu, Jianwei; Qian, Yang / A profile similarity-based personalized federated learning method for wearable sensor-based human activity recognition. November 2024; In: Information & Management. Vol. 61, No. 7
Xiong, Yingqiu; Liu, Yezheng; Qian, Yang; Jiang, Yuanchun; Chai, Yidong; Ling, Haifeng / Review-based recommendation under preference uncertainty: An asymmetric deep learning framework. August 2024; In: European Journal of Operational Research. Vol. 316, No. 3, pp. 1044-1057
Qian, Yang; Ling, Haifeng; Meng, Xiangrui; Jiang, Yuanchun; Chai, Yidong; Liu, Yezheng / Voice of the Professional: Acquiring competitive intelligence from large-scale professional generated contents. July 2024; In: Journal of Business Research. Vol. 180
Chai, Yidong; Liu, Yi; Li, Weifeng; Zhu, Bin; Liu, Hongyan; Jiang, Yuanchun / An interpretable wide and deep model for online disinformation detection. March 2024; In: Expert Systems with Applications. Vol. 237, No. Part B
Yu, Shuo; Chai, Yidong; Samtani, Sagar; Liu, Hongyan; Chen, Hsinchun / Motion Sensor–Based Fall Prevention for Senior Care: A Hidden Markov Model with Generative Adversarial Network Approach. March 2024; In: Information Systems Research. Vol. 35, No. 1, pp. 1-15
Gu, Dongxiao; Wang, Qin; Chai, Yidong; Yang, Xuejie; Zhao, Wang; Li, Min; Zolotarev, Oleg; Xu, Zhengfei; Zhang, Gongrang / Identifying the Risk Factors of Allergic Rhinitis Based on Zhihu Comment Data Using a Topic-Enhanced Word-Embedding Model: Mixed Method Study and Cluster Analysis. February 2024; In: Journal of Medical Internet Research. Vol. 26
Zhou, Fan; Jiang, Yuanchun; Qian, Yang; Liu, Yezheng; Chai, Yidong / Product consumptions meet reviews: Inferring consumer preferences by an explainable machine learning approach. February 2024; In: Decision Support Systems. Vol. 177
Chai, Yidong; Liang, Ruicheng; Samtani, Sagar; Zhu, Hongyi; Wang, Meng; Liu, Yezheng; Jiang, Yuanchun / Additive Feature Attribution Explainable Methods to Craft Adversarial Attacks for Text Classification and Text Regression. December 2023; In: IEEE Transactions on Knowledge and Data Engineering. Vol. 35, No. 12, pp. 12400-12414
Jing, Erkang; Liu, Yezheng; Chai, Yidong; Sun, Jianshan; Samtani, Sagar; Jiang, Yuanchun; Qian, Yang / A deep interpretable representation learning method for speech emotion recognition. November 2023; In: Information Processing and Management. Vol. 60, No. 6
Xie, Jiaheng; Chai, Yidong; Liu, Xiao / Unbox the Black-Box: Predict and Interpret YouTube Viewership Using Deep Learning. June 2023; In: Journal of Management Information Systems. Vol. 40, No. 2, pp. 541-579
CHAI, Yidong; LIU, Hongyan; XU, Jie; SAMTANI, Sagar; JIANG, Yuanchun; LIU, Haoxin / A Multi-Label Classification with an Adversarial-Based Denoising Autoencoder for Medical Image Annotation. June 2023; In: ACM Transactions on Management Information Systems. Vol. 14, No. 2
Qian, Yang; Jiang, Yuanchun; Shang, Jennifer; Chai, Yidong; Liu, Yezheng / Why some products compete and others don't: A competitive attribution model from customer perspective. June 2023; In: Decision Support Systems. Vol. 169
Ebrahimi, Mohammadreza; Chai, Yidong; Zhang, Hao Helen; Chen, Hsinchun / Heterogeneous Domain Adaptation With Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity. February 2023; In: IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 45, No. 2, pp. 1862-1875
Samtani, Sagar; Zhu, Hongyi; Padmanabhan, Balaji; Chai, Yidong; Chen, Hsinchun; Nunamaker Jr., Jay F. / Deep Learning for Information Systems Research. January 2023; In: Journal of Management Information Systems. Vol. 40, No. 1, pp. 271-301
Yu, Shuo; Chai, Yidong; Chen, Hsinchun; Sherman, Scott J.; Brown, Randall A. / WEARABLE SENSOR-BASED CHRONIC CONDITION SEVERITY ASSESSMENT: AN ADVERSARIAL ATTENTION-BASED DEEP MULTISOURCE MULTITASK LEARNING APPROACH. September 2022; In: MIS Quarterly. Vol. 45, No. 3, pp. 1355-1394
Qian, Yang; Xu, Wang; Liu, Xiao; Ling, Haifeng; Jiang, Yuanchun; Chai, Yidong; Liu, Yezheng / Popularity prediction for marketer-generated content: A text-guided attention neural network for multi-modal feature fusion. July 2022; In: Information Processing and Management. Vol. 59, No. 4
Li, Weifeng; Chai, Yidong / Assessing and Enhancing Adversarial Robustness of Predictive Analytics: An Empirically Tested Design Framework. June 2022; In: Journal of Management Information Systems. Vol. 39, No. 2, pp. 542-572
Ebrahimi, Mohammadreza; Chai, Yidong; Samtani, Sagar; Chen, Hsinchun / CROSS-LINGUAL CYBERSECURITY ANALYTICS IN THE INTERNATIONAL DARK WEB WITH ADVERSARIAL DEEP REPRESENTATION LEARNING. June 2022; In: MIS Quarterly. Vol. 46, No. 2, pp. 1209-1226
Samtani, Sagar; Chai, Yidong; Chen, Hsinchun / Linking Exploits from the Dark Web to Known Vulnerabilities for Proactive Cyber Threat Intelligence : An Attention-based Deep Structured Semantic Model. June 2022; In: MIS Quarterly. Vol. 46, No. 2, pp. 911-946
Chai, Yidong; Zhou, Yonghang; Li, Weifeng; Jiang, Yuanchun / An Explainable Multi-Modal Hierarchical Attention Model for Developing Phishing Threat Intelligence. March 2022; In: IEEE Transactions on Dependable and Secure Computing. Vol. 19, No. 2, pp. 790-803
Chai, Yidong; Bian, Yiyang; Liu, Hongyan; Li, Jiaxing; Xu, Jie / Glaucoma diagnosis in the Chinese context: An uncertainty information-centric Bayesian deep learning model. March 2021; In: Information Processing and Management. Vol. 58, No. 2
Yu, Shuo; Chai, Yidong; Chen, Hsinchun; Brown, Randall A.; Sherman, Scott J.; Nunamaker Jr., Jay F. / Fall Detection with Motion Sensors: A Hierarchical Attention-based Convolutional Neural Network Approach. 2021; In: Journal of Management Information Systems. Vol. 38, No. 4, pp. 1095-1121
Chai, Yidong; Liu, Hongyan; Xu, Jie / A new convolutional neural network model for peripapillary atrophy area segmentation from retinal fundus images. January 2020; In: Applied Soft Computing Journal. Vol. 86
Chai, Yidong; Liu, Hongyan; Xu, Jie / Glaucoma diagnosis based on both hidden features and domain knowledge through deep learning models. December 2018; In: Knowledge-Based Systems. Vol. 161, pp. 147-156
Chapters, Conference Papers, Creative and Literary Works
Liu, Haoxin; Zhang, Wenli; Xie, Jiaheng; Kim, Buomsoo; Zhang, Zhu; Chai, Yidong; Ram, Suhda / Few-Shot Learning for Chronic Disease Management: Leveraging Large Language Models and Multi-Prompt Engineering with Medical Knowledge Injection. January 2025; Proceedings of the 58th Hawaii International Conference on System Sciences. pp. 709-717
Chai, Yidong; Liu, Yi; Ebrahimi, Mohammadreza; Li, Weifeng; Padmanabhan, Balaji; Jiang, Yuanchun; Liu, Yezheng / Enhancing Adversarial Robustness: A Novel Bayesian Uncertainty-Based Ensemble Learning Method. August 2024; Proceeding - 2024 IEEE 9th International Conference on Data Science in Cyberspace, DSC 2024. pp. 329-336
Ebrahimi, Mohammadreza (Reza); Li, Weifeng; Chai, Yidong; Pacheco, Jason; Chen, Hsinchun / An Adversarial Reinforcement Learning Framework for Robust Machine Learning-based Malware Detection. November 2022; Proceedings - 22nd IEEE International Conference on Data Mining Workshops. pp. 567-576
Qian, Yang; Xiong, YingQiu; Wang, Yuyang; Jiang, Yuanchun; Liu, Yezheng; Chai, Yidong / Identification of Key Features for VR Applications with VREVIEW: A Topic Model Approach. April 2022; Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022. pp. 183-188
Xie, Jiaheng; Chai, Yidong; Liu, Xiao / An Interpretable Deep Learning Approach to Understand Health Misinformation Transmission on YouTube. January 2022; Proceedings of the 55th Annual Hawaii International Conference on System Sciences (HICSS 2022). pp. 1470-1479
Liu, Yezheng; Wang, Jicheng; Qian, Yang; Jiang, Yuanchun; Sun, Jianshan; Chai, Yidong / Dynamic Topic Model for Tracking Topic Evolution and Measuring Popularity of Scientific Literature. October 2021; Proceedings - 2021 IEEE Sixth International Conference on Data Science in Cyberspace, DSC 2021. pp. 315-320
Ebrahimi, Mohammadreza; Samtani, Sagar; Chai, Yidong; Chen, Hsinchun / Detecting cyber threats in non-english hacker forums: An adversarial cross-lingual knowledge transfer approach. December 2020; Proceedings - 2020 IEEE Symposium on Security and Privacy Workshops (SPW 2020). pp. 20-26
Chai, Yidong; Li, Weifeng / Towards deep learning interpretability: A topic modeling approach. December 2019; ICIS 2019 Proceedings.
Chai, Yidong; He, Luo; Mei, Qiuyan; Liu, Hongyan; Xu, Liang / Deep learning through two-branch convolutional neuron network for glaucoma diagnosis. 2017; Smart Health - International Conference, ICSH 2017, Proceedings. Vol. 10347 LNCS, pp. 191-201
Chai, Yidong; Liu, Hongyan; Zhang, Li / Extracting visual words from images for effective medical image analysis. 2017; Proceedings ot the 21st Pacific Asia Conference on Information Systems: "Societal Transformation Through IS/IT", PACIS 2017.
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