Publications

Qi Zhang, Dian Chen, Lance M. Kaplan, Audun Jøsang, Feng Chen, Dong Hyun Jeong, and Jin-Hee Cho. “X-MAP: eXplainable Misclassification Analysis and Profiling for Spam and Phishing Detection.” Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2026), Jun. 2026.

Xinyi Zhang, Mamtaj Akter, Heajun An, Minqian Liu, Qi Zhang, Lifu Huang, Jin-Hee Cho, Pamela J. Wisniewski, and Sang Won Lee. “From Vulnerable to Resilient: Examining Parent and Teen Perceptions on How to Respond to Unwanted Cybergrooming Advances.” ACM Conference on Human Factors in Computing Systems (CHI 2026), Apr. 2026.

Qi Zhang, Dian Chen, Lance M. Kaplan, Audun Jøsang, Feng Chen, Dong Jeong, and Jin-Hee Cho. “Beyond Binary Opinions: A Deep Reinforcement Learning-Based Approach to Uncertainty-Aware Competitive Influence Maximization.” IEEE Transactions on Network Science and Engineering, vol. 13, pp. 2219–2235, 2026.

Heajun An, Qi Zhang, Minqian Liu, Xinyi Zhang, Sang Won Lee, Lifu Huang, Pamela J. Wisniewski, and Jin-Hee Cho. “StagePilot: A Deep Reinforcement Learning Agent for Stage-Controlled Cybergrooming Simulation.” Proceedings of the 27th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL 2026).

Dian Chen, Qi Zhang, Lance Kaplan, Audun Josang, Donghyun Jeong, Feng Chen, and Jin-Hee Cho. “fair-LDP: Uncertainty-Guided Fairness and Privacy for Federated Healthcare Learning.” IEEE International Conference on Data Mining (ICDM 2025), Dec. 2025.

Minqian Liu, Zhiyang Xu, Xinyi Zhang, Heajun An, Sarvech Qadir, Qi Zhang, Pamela J. Wisniewski, Jin-Hee Cho, Sang Won Lee, Ruoxi Jia, and Lifu Huang. “LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models.” Conference on Language Modeling (COLM 2025), Oct. 2025.

Dian Chen, Qi Zhang, Lance Kaplan, Audun Josang, Donghyun Jeong, Feng Chen, and Jin-Hee Cho. “Ethical AI for Healthcare Systems: Uncertainty-Aware, Fair Federated Learning.” IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2025), Jun. 2025.

Qi Zhang, Lance M. Kaplan, Audun Jøsang, Dong Hyun Jeong, Feng Chen, and Jin-Hee Cho. “Uncertainty-Aware Influence Maximization: Enhancing Propagation in Competitive Social Networks with Subjective Logic.” 2024 IEEE International Conference on Big Data (BigData 2024), pp. 2065–2071, Dec. 2024.

Chen-Wei Chang, Shailik Sarkar, Shutonu Mitra, Qi Zhang, Hossein Salemi, Hemant Purohit, Fengxiu Zhang, Michin Hong, Jin-Hee Cho, and Chang-Tien Lu. “Exposing LLM Vulnerabilities: Adversarial Scam Detection and Performance.” IEEE BigData 2024 — Workshop on Big Data Engineering and Analytics in Cyber-Physical Systems (BigEACPS’24), Dec. 2024.

Shutonu Mitra, Qi Zhang, Chen-Wei Chang, Hossein Salemi, Hemant Purohit, Fengxiu Zhang, Michin Hong, Chang-Tien Lu, and Jin-Hee Cho. “Towards Inclusive Cybersecurity: Protecting the Vulnerable with Social Cyber Vulnerability Metrics.” The Sixth IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TSP) — Workshop on Inclusive AI for Online Cybersecurity, invited paper, Oct. 2024.

Zhen Guo, Zelin Wan, Qisheng Zhang, Xujiang Zhao, Qi Zhang, Lance M. Kaplan, Audun Jøsang, Dong H. Jeong, Feng Chen, and Jin-Hee Cho. “A survey on uncertainty reasoning and quantification in belief theory and its application to deep learning.” Information Fusion, vol. 101 (2024): 101987.

Zhen Guo, Qi Zhang, Qisheng Zhang, Lance M. Kaplan, Audun Jøsang, Feng Chen, Dong H. Jeong, and Jin-Hee Cho. “Detecting intents of fake news using uncertainty-aware deep reinforcement learning.” 2023 IEEE International Conference on Web Services (ICWS), pp. 722–724, Jul. 2023.

Zhen Guo, Qi Zhang, Qisheng Zhang, Lance Kaplan, Audun Jøsang, Feng Chen, Donghyun Jeong, and Jin-Hee Cho. “Uncertainty-Aware Reward-based Deep Reinforcement Learning for Intent Analysis of Social Media Information.” The 1st AAAI Workshop on Uncertainty Reasoning and Quantification in Decision Making (UDM-AAAI-23), co-located with AAAI-23, Feb. 2023.