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Dr

Jinran Wu

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Overview

Background

I am a research fellow in the School of Mathematics and Physics at the University of Queensland, Australia. I work with Professor Geoffrey J. McLachlan (Fellow of the Australian Academy of Science) on semi-supervised learning, specifically investigating missingness mechanisms and mixture modelling. I earned my PhD in 2022 from the Queensland University of Technology (QUT), under the joint supervision of Professor You-Gan Wang (biostatistician), Professor Kevin Burrage (applied mathematician), and Professor Yu-Chu Tian (computer scientist).

Following my doctoral studies, I was appointed as an Associate Lecturer at QUT, where I coordinated the course Modelling Dependent Data, covering topics such as time series analysis and longitudinal data modelling. I subsequently joined the Australian Catholic University as a Research Fellow, working with Professor Herbert W. Marsh (Fellow of the Academy of the Social Sciences in Australia and the British Academy of Social Sciences) on large-scale social survey data modelling, and also coordinated the course Interpreting Literature and Data.

My research focuses on machine learning and statistical modelling, with a particular emphasis on robust statistical methods and predictive analytics. I have published over 80 peer-reviewed papers in leading journals such as Pattern Recognition and several IEEE Transactions journals. My work has been cited over 1,450 times, and my current h-index is 22 (Google Scholar).

I currently serve as an Academic Editor for PLOS ONE and have guest-edited special issues for journals including Safety Science and Environmental Modelling & Assessment. I have acted as a frequent peer reviewer for over 50 leading journals, such as The New England Journal of Medicine and IEEE Transactions on Pattern Analysis and Machine Intelligence. Additionally, I have served as a grant reviewer for the German Academic Exchange Service.

I have served on program committees for major conferences such as the International Conference on Artificial Intelligence in Education and the Australasian Data Science and Machine Learning Conference. I actively engage in international research collaborations with scholars from leading institutions, including the University of Oxford (UK), the University of Munich (Germany), Michigan State University (US), and Xi’an Jiaotong University (China).

In 2022, I received the Chinese Government Award for Outstanding Self-Financed Students Abroad, a highly competitive distinction granted by the China Scholarship Council to acknowledge the top 500 Chinese scholars studying overseas.

Availability

Dr Jinran Wu is:
Available for supervision

Qualifications

  • Doctor of Philosophy of Statistics, Queensland University of Technology

Works

Search Professor Jinran Wu’s works on UQ eSpace

94 works between 2017 and 2025

81 - 94 of 94 works

2021

Journal Article

A cloud endpoint coordinating CAPTCHA based on multi-view stacking ensemble

Ouyang, Zhiyou, Zhai, Xu, Wu, Jinran, Yang, Jian, Yue, Dong, Dou, Chunxia and Zhang, Tengfei (2021). A cloud endpoint coordinating CAPTCHA based on multi-view stacking ensemble. Computers & Security, 103 102178, 1-17. doi: 10.1016/j.cose.2021.102178

A cloud endpoint coordinating CAPTCHA based on multi-view stacking ensemble

2021

Journal Article

Influential factors on Chinese airlines’ profitability and forecasting methods

Xu, Xu, McGrory, Clare Anne, Wang, You-Gan and Wu, Jinran (2021). Influential factors on Chinese airlines’ profitability and forecasting methods. Journal of Air Transport Management, 91 101969, 1-8. doi: 10.1016/j.jairtraman.2020.101969

Influential factors on Chinese airlines’ profitability and forecasting methods

2021

Journal Article

A hybrid rolling grey framework for short time series modelling

Cui, Zhesen, Wu, Jinran, Ding, Zhe, Duan, Qibin, Lian, Wei, Yang, Yang and Cao, Taoyun (2021). A hybrid rolling grey framework for short time series modelling. Neural Computing and Applications, 33 (17), 11339-11353. doi: 10.1007/s00521-020-05658-0

A hybrid rolling grey framework for short time series modelling

2020

Conference Publication

Improved Whale Optimization Algorithm via Cellular Automata

Gao, Yuchao, Qian, Cheng, Tao, Zhenghang, Zhou, Hu, Wu, Jinran and Yang, Yang (2020). Improved Whale Optimization Algorithm via Cellular Automata. 2020 IEEE International Conference on Progress in Informatics and Computing (PIC), Shanghai, China, 18-20 December 2020. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/pic50277.2020.9350796

Improved Whale Optimization Algorithm via Cellular Automata

2020

Conference Publication

A robust decomposition-ensemble framework for wind speed forecasting

Zhang, Bingquan, Yang, Yang, Zhao, Dengli and Wu, Jinran (2020). A robust decomposition-ensemble framework for wind speed forecasting. 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV), Shenzhen, China, 13-15 December 2020. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/icarcv50220.2020.9305351

A robust decomposition-ensemble framework for wind speed forecasting

2020

Conference Publication

Modified Slime Mould Algorithm via Levy Flight

Cui, Zhesen, Hou, Xiaolei, Zhou, Hu, Lian, Wei and Wu, Jinran (2020). Modified Slime Mould Algorithm via Levy Flight. 2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), Chengdu, China, 17-19 October 2020. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/cisp-bmei51763.2020.9263669

Modified Slime Mould Algorithm via Levy Flight

2020

Journal Article

Multi-horizon accommodation demand forecasting: a New Zealand case study

Zhu, Min, Wu, Jinran and Wang, You-Gan (2020). Multi-horizon accommodation demand forecasting: a New Zealand case study. International Journal of Tourism Research, 23 (3), 442-453. doi: 10.1002/jtr.2416

Multi-horizon accommodation demand forecasting: a New Zealand case study

2020

Journal Article

Identifying barley pan-genome sequence anchors using genetic mapping and machine learning

Gao, Shang, Wu, Jinran, Stiller, Jiri, Zheng, Zhi, Zhou, Meixue, Wang, You-Gan and Liu, Chunji (2020). Identifying barley pan-genome sequence anchors using genetic mapping and machine learning. Theoretical and Applied Genetics, 133 (9), 2535-2544. doi: 10.1007/s00122-020-03615-y

Identifying barley pan-genome sequence anchors using genetic mapping and machine learning

2020

Journal Article

Adaptive resilient control of a class of nonlinear systems based on event-triggered mechanism

Yang, Yang, Ge, Jingzhi, Yue, Dong, Meng, Qing and Wu, Jinran (2020). Adaptive resilient control of a class of nonlinear systems based on event-triggered mechanism. Neurocomputing, 403, 304-313. doi: 10.1016/j.neucom.2020.04.061

Adaptive resilient control of a class of nonlinear systems based on event-triggered mechanism

2020

Journal Article

An improved firefly algorithm for global continuous optimization problems

Wu, Jinran, Wang, You-Gan, Burrage, Kevin, Tian, Yu-Chu, Lawson, Brodie and Ding, Zhe (2020). An improved firefly algorithm for global continuous optimization problems. Expert Systems with Applications, 149 113340, 1-12. doi: 10.1016/j.eswa.2020.113340

An improved firefly algorithm for global continuous optimization problems

2020

Book Chapter

Improved Grey Model by Dragonfly Algorithm for Chinese Tourism Demand Forecasting

Wu, Jinran and Ding, Zhe (2020). Improved Grey Model by Dragonfly Algorithm for Chinese Tourism Demand Forecasting. Lecture Notes in Computer Science. (pp. 199-209) Cham: Springer International Publishing. doi: 10.1007/978-3-030-55789-8_18

Improved Grey Model by Dragonfly Algorithm for Chinese Tourism Demand Forecasting

2019

Journal Article

A new hybrid model to predict the electrical load in five states of Australia

Wu, Jinran, Cui, Zhesen, Chen, Yanyan, Kong, Demeng and Wang, You-Gan (2019). A new hybrid model to predict the electrical load in five states of Australia. Energy, 166, 598-609. doi: 10.1016/j.energy.2018.10.076

A new hybrid model to predict the electrical load in five states of Australia

2017

Journal Article

A novel hybrid model based on extreme learning machine, k-nearest neighbor regression and wavelet denoising applied to short-term electric load forecasting

Li, Weide, Kong, Demeng and Wu, Jinran (2017). A novel hybrid model based on extreme learning machine, k-nearest neighbor regression and wavelet denoising applied to short-term electric load forecasting. Energies, 10 (5) 694, 1-16. doi: 10.3390/en10050694

A novel hybrid model based on extreme learning machine, k-nearest neighbor regression and wavelet denoising applied to short-term electric load forecasting

2017

Journal Article

A New Hybrid Model FPA-SVM Considering Cointegration for Particular Matter Concentration Forecasting: A Case Study of Kunming and Yuxi, China

Li, Weide, Kong, Demeng and Wu, Jinran (2017). A New Hybrid Model FPA-SVM Considering Cointegration for Particular Matter Concentration Forecasting: A Case Study of Kunming and Yuxi, China. Computational Intelligence and Neuroscience, 2017 2843651, 1-11. doi: 10.1155/2017/2843651

A New Hybrid Model FPA-SVM Considering Cointegration for Particular Matter Concentration Forecasting: A Case Study of Kunming and Yuxi, China

Supervision

Availability

Dr Jinran Wu is:
Available for supervision

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Media

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