Frank XING
Visiting Assistant Professor- Ph.D. (Computer Science, Nanyang Technological University)
- B.Sc. (Information Systems & Economics, Peking University)
Frank Xing is an assistant professor in the Department of Information Systems and Analytics at the School of Computing, National University of Singapore (NUS). Prior to joining NUS, he was a NTU Presidential Postdoctoral Fellow and worked in industry for a year. He earned his bachelor's degrees in Information Systems and Economics from Peking University, and a PhD in Computer Science and Engineering from Nanyang Technological University. Dr. Xing's research interest lies in natural language processing and predictive analytics, with a special focus on financial applications. He passionately studies how human knowledge can be represented and engineered to support decision-making, and what consequences would knowledge-driven algorithms and systems cause to our society. He has served as guest editors for journals, e.g., IEEE Transactions on Artificial Intelligence, and area chairs for conferences, e.g., International Conference on Computational Linguistics. His research has also been featured by news media, e.g., Dow Jones. To know more about current and past projects, please visit: https://frank-xing.info
RESEARCH AREAS
RESEARCH INTERESTS
Financial forecasting and optimization models
Knowledge management
Social impact of artificial intelligence
RESEARCH PROJECTS
RESEARCH GROUPS
TEACHING INNOVATIONS
SELECTED PUBLICATIONS
- "Incorporating multiple knowledge sources for targeted aspect-based financial sentiment analysis", ACM Transactions on Management Information Systems (2023)
- "Does social media sentiment predict Bitcoin trading volume?", ICIS (2022)
- "Financial sentiment analysis: An investigation into common mistakes and silver bullets", COLING (2020)
- "Growing semantic vines for robust asset allocation", Knowledge-Based Systems (2019)
- "Intelligent asset allocation via market sentiment views", IEEE Computational Intelligence Magazine (2018)
AWARDS & HONOURS
MODULES TAUGHT