Short Bio

Zixuan Yuan is an Assistant Professor at the FinTech Thrust, HKUST (Guangzhou). He received his Ph.D. in Management (Information Technology track) from Rutgers University. His research interests lie in the general area of data mining and artificial intelligence, particularly in text mining, graph learning, self-supervised learning, and model interpretability, as well as their applications in analyst report analysis, quantitative trading, event-driven investing, and knowledge graph construction & reasoning. He has research experience in multiple industrial research labs, such as IBM Research, Baidu Research, and RavenPack. He has published in refereed journals and conference proceedings, such as IEEE TKDE, IEEE IOTJ, ACM SIGKDD, SIGIR, WWW, AAAI, and IJCAI.

Multiple positions are available for self-motivated Ph.D. students and RAs. Visiting students are also welcome. Please check here for more information. Thanks!

Research Interest:

• LLM-driven Financial Text Mining
• Graph Learning
• Self-supervised Learning
• Interpretable AI

Education

• Ph.D. in Data Mining and Business Analytics
University: Rutgers, The State University of New Jersey
Years: 2018-2023
Advisor: Prof. Hui Xiong

• M.S. in Information Technology
University: Rutgers, The State University of New Jersey
Years: 2015-2017
Advisor: Prof. Hui Xiong

• B.S. in Economics
University: Tongji University
Years: 2011-2015

Teaching

Past Courses

• Hong Kong University of Science and Technology (Guangzhou)
  [2023 Fall] FTEC 5050 Machine Learning and Artificial Intelligence
  
• Rutgers University
  [2023 Spring] 29:623:335:01 Data Warehousing and Data Mining
  
[2022 Summer] 29:623:311:B7 Production and Operations Management

Conference PC Member & Reviewer

• The AAAI Conference on Artificial Intelligence (AAAI), 2023, 2024, 2025
• ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2024, 2025
• The IEEE ICDM NeuRec-Workshop, 2023
• ACM International Conference on AI in Finance (ICAIF), 2025
• The International Conference on Information Systems (ICIS), 2024

Journal Reviewer

• Transactions on Knowledge Discovery from Data (TKDD), 2022
• Frontiers of Computer Science, 2022
• Computer Communications, 2022
• World Wide Web, 2022

News

• [Sep. 2024] One papers got accepted to WINE’24.
• [May. 2024] Two papers got accepted to KDD’24.
• [May. 2024] One papers got accepted to IJCAI'24.
• [Dec. 2023] One paper on multi-label classification got accepted to AAAI’24.
• [Nov. 2023] One paper on stock trading got accepted to IEEE TKDE.
• [Oct. 2023] One paper on earnings call analysis got accepted to ACM ICAIF’23.
• [Aug. 2023] Invited as a PC member for AAAI’24.
• [Nov. 2023] Joined HKUST as an assistant professor in FinTech Thrust.
• [Aug. 2022] Invited as a PC member for AAAI’23.
• [Aug. 2022] One paper on product representation learning got accepted to IEEE TKDE.
• [Apr. 2022] Served as a session chair at INFORMS’22.
• Show more
[Dec. 2021] One paper on KG reasoning got accepted to AAAI’22 (15% acceptance rate).
[May. 2021] Two papers got accepted to KDD’21.
[Mar. 2021] Passed my dissertation proposal defense, pleased to be Ph.D. candidate now!
[Jun. 2021] Joined IBM Watson Research Lab as a research intern.
[Jan. 2021] One paper accepted to WWW’21.
[Dec. 2020] Joined RavenPack as a data scientist intern.
[Dec. 2020] One paper accepted to AAAI’21.
[Apr. 2020] One paper accepted to SIGIR’21.

Publications [Google Scholar][ResearchGate]

* means equal contribution.
† means corresponding authors.

Prospective Students

• Regular Ph.D. Admission
  Eligible Candidates: Undergraduate or Master students
  Enrollment: 2025 Academic Year
  Funding: HKUST Ph.D. Scholarship or Assistantship (around 15K RMB per month)
  Advisorship: Advised by Dr. Zixuan Yuan or co-advised by Dr. Zixuan Yuan and Dr. Hui Xiong
  
• Research Assistant or Intern
  For HKUST students: feel free to drop me an email or stop by my office.
  For other students: please attach your CV to your email, and demonstrate clearly your research interests & how you can collaborate with me.
  
• Ph.D. Student Requirements
  1. With a bachelor’s or master’s degree in Computer Science, Mathematics, Statistics, Finance, or other related disciplines.
  2. Have a strong passion for academic research, a thirst for knowledge, curiosity, and enjoyment of the investigative process.
  3. Hard working and a high sense of responsibility.
  4. Excellent communication skills and proficiency in English.
  

Contact

Address: HKUST (GZ)
Office Location: E3（C9）L5 502
Email: zixuanyuan@hkust-gz.edu.cn