Qin, Yu
Qin, Yu 秦宇
BS (Renmin); PhD (Renmin); PhD (ASU)
Assistant Professor
Contact
Department of Decisions, Operations and Technology
9/F, Cheng Yu Tung Building
12 Chak Cheung Street
Shatin, N.T., Hong Kong
+852 3943 7813 / +852 3943 1708
Biography
Professor Yu Qin is an Assistant Professor in the Department of Decisions, Operations and Technology at the Chinese University of Hong Kong (CUHK) Business School. He holds a Ph.D. in Business Administration from the W.P. Carey School of Business at Arizona State University and a Ph.D. in Computer Science from Renmin University of China, where he also earned his B.S. in Computer Science and B.Econ. in Financial Technology. His research focuses on designing and developing deep learning algorithms for predictive analytics in business contexts, specialising in multimodal computing and natural language processing. Additionally, he develops interpretation methods for Large Language Models (LLMs) to support responsible and trustworthy LLM applications in management science.
Teaching Areas
Information Systems
Database Management
Research Interests
FinTech
Multimodal Modeling
Natural Language Processing
Large Language Model Interpretation
Publications & Working Papers
- Yi Yang, Yu Qin, Yangyang Fan, and Zhongju Zhang (2023), “Unlocking the Power of Voice for Financial Risk Prediction: A Theory-Driven Deep Learning Design Approach,” MIS Quarterly, 47(1).
- Zhen Ye, Yu Qin, and Wei Xu (2020), “Financial Risk Prediction with Multi-Round Q&A Attention Network,” Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI’20).
- Yu Qin and Yi Yang (2019), “What You Say and How You Say It Matters: Predicting Stock Volatility Using Verbal and Vocal Cues,” Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL’19).
- Yu Qin, Paul J. Hu, and Olivia R. Liu Sheng (Working), “Cross-Document Modeling for Financial Risk Predictions: A Concept-Guided Deep Learning Method”.
- Tianyi Li, Yu Qin, and Olivia R. Liu Sheng (Working), “A Multi-Task Evaluation of LLMs’ Processing of Academic Text Input”.
- Yu Qin and Olivia R. Liu Sheng (Working), “Uncovering the Internal Mechanisms of Large Language Models in Decision-Making under Risk”.
Awards & Honours
- Best Student Paper Award Runner-Up, Workshop on Information Technologies and Systems (WITS), 2025
Academic/Professional Services
- Program Committee Member, Workshop on Information Technologies and Systems, 2026
Financial Times Masters in Finance 2026 Pre-experience Programmes Ranking