Jing (Roy) Yang 杨靖
researcher, process mining, predictive analytics, visual analytics
I’m a postdoctoral research fellow at Queensland University of Technology (QUT), Australia. I’m interested in discovering knowledge from process execution data to support improved decision-making, especially knowledge about (human) resources.
My current research focuses on mining organizational models from process execution data and applying them to workforce analytics [read more].
I’m also involved in Foragecaster, a project that aims at delivering a planner system, powered by accurate and reliable machine learning models, to support farmers in decisions on forage, grazing livestock, and farm sustainability.
I’m a member of the Explainable Analytics for Machine Intelligence (XAMI) Lab at QUT.
Education
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Ph.D. (2023), Queensland University of Technology, Australia
Thesis title: “Discovering Organizational Models from Event Logs for Workforce Analytics”, advised by Chun Ouyang, Arthur ter Hofstede, and Wil van der Aalst. An e-copy of my doctoral thesis can be download via [this link]. -
Master 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), advised by Yang Yu. -
Bachelor degree in Software Engineering (2016), Sun Yat-sen University, China
Honors and Awards
- Graduate of Merit, Food Agility, 2023
- Australian Commonwealth Research Training Program (Scholarship), 2019-2023
- Top-up Scholarship, Food Agility, 2021-2022
- High-Achiever Higher Degree Research Student, QUT, March 2022
- Excellent Master Student Award, Sun Yat-sen University, 2018
- Meritorious Winner (
Team 37861) the Mathematical Contest in Modelling, Consortium for Mathematics and Its Applications (COMAP), 2015
What's new
| 2023/11 |
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| 2023/10 |
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| 2023/09 |
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