Projects - Presidential Chair Professor, Area Head of Information Systems & Operations Management (Co-Chair), Director of MSc Programme in Information Management and Business Analytics (IM Concentration), Director of Center on Blockchain and Intelligent Technology (CBIT) of Shenzhen Institute of Data Economics

J. Leon ZHAO

Title:

Presidential Chair Professor, Area Head of Information Systems & Operations Management (Co-Chair), Director of MSc Programme in Information Management and Business Analytics (IM Concentration), Director of Center on Blockchain and Intelligent Technology (CBIT) of Shenzhen Institute of Data Economics

Education Background:

Ph. D. in Information Systems, Haas School of Business, UC Berkeley
M. S. in Engineering, UC Davis
B. S. in Engineering, Beijing University of Agricultural Engineering

leonzhao@cuhk.edu.cn

Office Address

Phone

Teaching Area

Information Systems

Other

2025《信息技术前沿》论文：生成式人工智能：不断演进的技术、日益增强的社会影响以及信息系统研究的机遇 Link to 推文 https://cbit.cuhk.edu.cn/paper2025 和原文 https://doi.org/10.1007/s10796-025-10581-7

Research

Agentic Workflow, Big Data Applications, Blockchain Applications, Business Applications of GenAI, Design Science Research, Human-AI Collaboration, FinTech

Personal Website

https://scholar.google.com/citations?user=qCyjuogAAAAJ

LLM BizApp

References

https://www.datacamp.com/blog/top-open-source-llms

https://www.techopedia.com/12-practical-large-language-model-llm-applications

https://builtin.com/artificial-intelligence/large-language-model-application-development

https://www.datatobiz.com/blog/guide-to-llm-based-model-development/

https://github.blog/2023-10-05-a-developers-guide-to-open-source-llms-and-generative-ai/

https://neurosys.com/blog/10-practical-applications-of-large-language-models-in-business

https://research.aimultiple.com/large-language-models-examples/

Junyi Li, Xiaoxue Cheng, Xin Zhao, Jian-Yun Nie, and Ji-Rong Wen. 2023. HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 6449–6464, Singapore. Association for Computational Linguistics.

https://aclanthology.org/2023.emnlp-main.397.pdf