Siyuan (Bruce) JIN (金思远) is a fourth-year PhD candidate in HKUST Business School, majoring in Information Systems (IS). He is fortunate to be advised by Prof. Kar Yan Tam.
His research interests center on 1) blockchain infrastructure and application governance and 2) AI use in enterprise IT management. He applies econometric and experimental methods to tackle questions in these fields. He received the China National Scholarship in 2020, Hong Kong PhD Fellowship (HKPFS) award in 2024, and Young Scientists Program Award in 2025. His papers have been accepted by top IS conferences, including International Conference on Information Systems (ICIS), Conference on Information Systems and Technology (CIST), and Statistical Challenges in Electronic Commerce Research (SCECR). His papers are nominated as best paper of ICIS 2024 and ICIS 2025. He has contributed to policy papers for the Hong Kong Monetary Authority (HKMA) and received a 2025 NSFC Young Student Basic Research Program (PhD Student) Grant (2026-2027, 300,000) RMB). He has organized over 40 IS online PhD student seminars.
Before HKUST, he spent two years as a trainee and a full-stack engineer at HSBC IT Architecture and HSBC Laboratory, respectively, developing Blockchain projects. His work earned the 2021 Top Performer award, 2021 Role Model honor, and finalist status in the 2021 Global CBDC Challenge by the Monetary Authority of Singapore.
News
IS Paper Sharing Group
Inspired by open talks in other subjects, we organize an information systems paper sharing series. Our initial targeted audience is mainly PhD students. We also welcome faculty members and industry practitioners to share more advanced topics in this area. You can email me (siyuan.jin@connect.ust.hk) if you want to join us. [Details]
Research Assistant Recruitment
We are hiring a part-time Research Assistant (remote) with a Computer Science (or related) background to support blockchain/AI research projects, focusing on data scraping (building and maintaining web scrapers, automating data collection and cleaning) and data analytics (processing large datasets, exploratory analysis, basic econometrics). Strong Python (or R) skills, experience with web scraping tools, and solid data statistics are required; familiarity with blockchain/Ethereum data is a plus but not mandatory. The position is part-time with flexible hours and can be remote, and it offers approximately double the average RA pay at our institution. Interested candidates should email siyuan.jin@connect.ust.hk with a CV, a brief description of relevant experience, and (optionally) a code sample or GitHub link.
Contact
- Email: siyuan.jin@connect.ust.hk