Evaluation Criteria

Evaluation Criteria

All components will be evaluated using the ADVICE criteria. A detailed rubric will be provided to registered participants.

• Automation: Automated workflow for replicability, simplicity, and accessibility for model implementation
• Digitalisation: Use of digital technologies to enhance integration and traceability
• Visualisation: Result presentation and demonstration by neat visualisation
• Innovation: Technological innovation in data preparation, model computation, and result validation.
• Comprehension: Comprehensive understanding of technical challenges and solutions.
• Efficiency: Computation efficiency for rapid and accurate modelling

Evaluation Committee

Local Committee (To be updated)

• Qianbing Zhang – Monash University
• Xilin Chen – Monash University
• Zhihang Li – Monash University
• Yimo Zhu – Monash University
• Xuzhen He – University of Technology Sydney
• Amanda Huang – Swinburne University of Technology
• Jurij Karlovsek – University of Queensland
• Chengguo Zhang – University of New South Wales
• An’nan Zhou – RMIT University

Scientific Committee (To be updated)

• Qing Ai – Shanghai Jiao Tong University, China
• Jian Chen – Huazhong University of Technology, China
• Georg Erharter – NGI, Norway
• Ke Ma – Dalian University of Technology, China
• Jelena Ninic – University of Birmingham, UK
• Yue Pan – Shanghai Jiao Tong University, China
• Brian Sheil – University of Cambridge, UK
• Huaina Wu – Hunan University, China
• Wei Wu – Nanyang Technological University, Singapore
• Nuwen Xu – Sichuan University, China
• Zhenhao Xu – Shandong University, China
• Yadong Xue – Tongji University, China
• Haitao Yu – Tongji University, China
• Mingliang Zhou – Tongji University, China
• Huamei Zhu – University of Birmingham, UK