已发表期刊论文（*Corresponding Author）

• Gang Chen, Lihua Huang, Shuaiyong Xiao^*, Chenghong Zhang, and Huimin Zhao. Attending to Customer Attention: A Novel Deep Learning Method for Leveraging Multimodal Online Reviews to Enhance Sales Prediction. Information Systems Research, 2024, 35(2), 829-849.
• Gang Chen, Shuaiyong Xiao^*, Chenghong Zhang, and Huimin Zhao. A Theory-driven Deep Learning Method for Voice-chat-based Customer Response Prediction. Information Systems Research, 2023, 34(4), 1513-1532.
• Liqian Bao, Gang Chen*, Zongxi Liu, Shuaiyong Xiao, and Huimin Zhao. Predicting Reward-Based Crowdfunding Success with Multimodal Data: A Theory-Guided Framework. Information & Management, 2025, 62(4), 104131.
• Shuaiyong Xiao, Jianxiong Wang, Jiwei Wang, Runlin Chen, and Gang Chen^*. On the Consensus of Synchronous Temporal and Spatial Views: A Novel Multimodal Deep Learning Method for Social Video Prediction. Information Processing and Management, 2024, 61(1), 103534.
• Jie Lin, Xueyu Liu^*, Shuaiyong Xiao, and Haowen Lin. Exploring Customer Satisfaction Across Language Backgrounds: A Hybrid Framework on Multilingual eWOM. Journal of Electronic Commerce Research, 2024, 25(3), 191-208.
• Zongxiang Zhang, Gang Chen, Yunjie Xu, Lihua Huang, Chenghong Zhang*, and Shuaiyong Xiao. FedDQA: A Novel Regularization-Based Deep Learning Method for Data Quality Assessment in Federated Learning. Decision Support Systems, 2024, 180, 114183.
• Gang Chen, Xiangge Li, Shuaiyong Xiao, Chenghong Zhang*, and Xianghua Lu. RACL: A Robust Adaptive Contrastive Learning for Conversational Satisfaction Prediction. Pattern Recognition, 2023, 138, 109386.
• Shuaiyong Xiao, Gang Chen, Chenghong Zhang*, and Xiangge Li. Complementary or Substitutive? A Novel Deep Learning Method to Leverage Text-image Interactions for Multimodal Review Helpfulness Prediction, Expert Systems with Applications, 2022, 118138.
• Gang Chen, Shuaiyong Xiao, Chenghong Zhang*, and Wei Wang. An orthogonal-space-learning-based method for selecting semantically helpful reviews. Electronic Commerce Research and Applications, 2022, 53, 101154.
• 金旭磊,陈刚*,黄丽华,肖帅勇,张成洪. 大模型的商业化应用：现状，挑战与对策, 工程管理科技前沿, 录用待发表.
• 张成洪,肖帅勇*,陆天,卢向华,黄丽华. 基于校园消费数据分析大学生网络借贷行为:借款倾向、消费变化与违约风险. 系统工程理论与实践. 2021, 41(03): 574-586.

研究项目

• 2024.1-2026.12，面向客户价值挖掘的可解释多模态深度学习方法研究，国家自然科学基金青年项目，主持
• 2021.12-2024.11，工业时序数据强机理数据分析算法研究（子课题），科技部重点研发计划，主持
• 2022.12-2025.4，基于层级关联约束的可解释深度学习方法及其在人机协同医疗诊断中的应用效果研究,中国博士后科学基金面上项目，主持
• 2021.10-2023.9，面向多源多模态中医药数据基于深度学习的疾病诊断方法研究，广东省中医药信息化重点实验室开放课题，主持
• 2025.1-2029.12，数据驱动的国家宏观医疗政策设计理论及动态优化，国家自然科学基金重大项目，参与
• 2023.1-2026.12，联邦学习应用实施中的数据质量风险防范与参与激励方法研究，国家自然科学基金面上项目，参与
• 2025.1-2028.12，线上专业服务的用户交互模式研究：基于社会化感知视角，国家自然科学基金面上项目，参与
• 2020.1-2023.12，基于可解释深度学习的知识挖掘方法及其应用研究，国家自然科学基金面上项目，参与
• 2023.12-2024.5，上海钢联大宗商品可解释人工智能预测系统总体设计，上海钢联，参与

工作经历

• 2025 至今，同济大学经济与管理学院，副教授
• 2022-2025，同济大学经济与管理学院，博士后
• 2021-2022，复旦大学计算机科学技术学院，博士后

学术服务

• 期刊审稿人：Information Systems Research, Information Processing and Management, Electronic Commerce Research, International Journal of Business Information Systems
• 会议审稿人：ICIS, PACIS, AMCIS, CSWIM, WITS
• PC member：ICSF 2025, WITS 2024

• 2021，复旦大学优秀毕业生