Roy Jing Yang 杨靖
researcher, process mining, data science
I am a postdoctoral research fellow at Queensland University of Technology (QUT), Australia. I’m interested in process mining, business process management, and trustworthy AI systems engineering.
My research on process mining focuses on organizational mining to support reliable workforce decisions and enhance process orchestration with human and autonomous software agents.
My research work also extends into agricultural data science. I’m a key contributor to Foragecaster, a project that aims at developing an AI-powered planner system to support farmers’ decisions on forage, grazing livestock, and farm sustainability. I lead the research on data quality and explainability, where we develop systematic methods to evaluate key farm production data, address data quality issues, and investigate their root causes to improve future data management and ensure effective use of machine learning models in a data-centric way.
Education
- Ph.D. (2023), Queensland University of Technology, Australia
Thesis title: Discovering Organizational Models from Event Logs for Workforce Analytics. Advisors: Chun Ouyang, Arthur ter Hofstede, and Wil van der Aalst.- An e-copy of my doctoral thesis can be downloaded via [this link]
- TL;DR 5-page “Extended Abstract” via [this link]
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Master’s degree in Computer Science and Technology (2019), Sun Yat-sen University, China
Thesis title: An Organizational Mining Method for Supporting Business Process Redesign (in Chinese). Advisor: Yang Yu. - Bachelor’s degree in Software Engineering (2016), Sun Yat-sen University, China
Honors and Awards
- Best BPM Dissertation Award 2024, International Conference on Business Process Management
- Outstanding Doctoral Thesis Award (ODTA) for 2023, QUT
- Graduate of Merit, Food Agility
What's new
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| 2026/07 |
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| 2026/06 |
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