Siyuan (Bruce) JIN (金思远) is a fourth-year PhD candidate in Information Systems at HKUST Business School, advised by Prof. Kar Yan Tam.
His current research interests center on 1) blockchain infrastructure and application governance and 2) AI use in enterprise IT management. His methods include data analytics, econometrics, and experimental methods. 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 HKET (經濟日報), and has industrial collaboration with HSBC, NetEase, Shanbei, and other companies.
He received the China National Scholarship (2020), Hong Kong PhD Fellowship (HKPFS) (2024), and Young Scientists Program Award (2025). He was also awarded the 2025 NSFC Young Student Basic Research Program Grant (300,000 RMB). He has organized 40+ online IS PhD student seminars.
Before HKUST, he worked for two years at HSBC as a trainee and full-stack engineer, focusing on blockchain projects in IT Architecture and the HSBC Laboratory. He received the 2021 Top Performer and Role Model awards, and was a finalist in the 2021 Global CBDC Challenge.
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