郑煜钒 (Yufan Ivan ZHENG)

Research Interest

My research focuses on developing useful tools that help humans make better decisions in different areas (healthcare, industry, public health, and social media) and exploring potential relationships between mass data. Relevant areas include but are not limited to: Data mining, Machine learning, Network science, Dynamic systems, Computational epidemiology, and Time series.

Ongoing/Main Research

Data-Driven Models for Epidemic Prediction, Prevention, and Intervention Evaluation.

Currently, infectious disease prevention and control and prediction face challenges such as diverse data sources, incomplete data, and complex systems. To effectively respond to the epidemic, it is necessary to integrate multi-source data and adopt a variety of modeling and analysis methods to achieve prevention, prediction, and intervention of the epidemic.

This research framework aims to improve the understanding and control of epidemic spread through database integration, statistical and machine learning modeling, dynamic system prediction, and intervention effect evaluation. This framework is not only suitable for the analysis of high-uncertainty time series data, but can also be extended to other complex systems that require real-time modeling.

Data-Driven Decision Models for Forest Biosecurity.

Ensuring pest area freedom is vital for trade, requiring robust, statistically supported evidence. This involves integrating large datasets from government, industry, and community surveillance, leveraging advanced computational techniques to support biosecurity market access, and optimizing surveillance strategies.

This project aims to create a comprehensive catalogue of forest pest surveillance and diagnostic data collected through targeted and general biosecurity efforts at regional and national levels. The primary objectives are to assess the suitability of these data for biosecurity purposes and explore how it can be integrated and analysed to achieve the following outcomes:

1. Provide statistical measures of pest area freedom,
2. Identify where surveillance or diagnostic data could guide areas for improvement in biosecurity systems/programs.

Publication

Journal Papers:

1. Impact of human mobility and weather conditions on Dengue mosquito abundance during the COVID-19 pandemic in Hong Kong
   Yufan Zheng, Keqi Yue, Eric Wong, Hsiang-Yu Yuan
   Infectious Disease Modelling (JCR Q1) | April 2025
   
   

2. A data-driven study of active meteorological stations and the factors motivating their establishing
   Choujun Zhan, Wei Jiang, Yufan Zheng, Junhui Lu Qizhi Zhang
   Sustainable Energy Technologies and Assessments (JCR Q1) | April 2023
   
   

3. Modeling the Spread Dynamics of Multiple-variant Coronavirus Disease under Public Health Interventions: A General Framework
   Choujun Zhan, Yufan Zheng, Lujiao Shao, Guanrong Chen, Haijun Zhang
   Information Sciences (JCR Q1) | February 2023
   
   

4. Random-Forest-Bagging Broad Learning System with Applications for COVID-19 Pandemic
   Choujun Zhan, Yufan Zheng, Haijun Zhang, Quansi Wen
   IEEE Internet of Things Journal (JCR Q1) | Mar 2021
   
   

5. Identifying epidemic spreading dynamics of COVID-19 by pseudocoevolutionary simulated annealing optimizers
   Choujun Zhan, Yufan Zheng, Zhikang Lai, Tianyong Hao, Bing Li
   Neural Computing and Applications (JCR Q2) | Mar 2020
   
   

Conference Papers:

1. Ensemble Learning for Crowdfunding Dynamics: JingDong Crowdfunding Project
   Hu Ming, Kaihan Wu, Minghao Tan, Yufan Zheng, Junyan Lin, Choujun Zhan
   International Conference on Neural Computing for Advanced Applications 2021 (NCAA 2021) | Oct 2022
   
   

2. COVID-19’s Impact on the Box Office: Machine Learning and Difference-in-Difference
   Yufan Zheng, Qiaoling Zhen, Minghao Tan, Haoran Hu, Choujun Zhan
   2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) | Nov 2021
   
   

3. Detection Capability Prediction Based on Broad Learning System During The COVID-19 Pandemic
   Junyan Lin, Minghao Tan, Yufan Zheng, Kaihan Wu, Choujun Zhan
   2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) | Nov 2021
   
   

4. Predicting video game sales based on machine learning and hybrid-based feature selection
   Jianbing Li, Yufan Zheng, Haoran Hu, Junhui Lu, Choujun Zhan
   2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) | Nov 2021
   
   

5. The impact of COVID-19 on online games: Machine learning and Difference-In-Difference
   Shuangyan Wu, Haoran Hu, Yufan Zheng, Qiaoling Zhen, Shuntao Zhang, Choujun Zhan
   CCF Conference on Computer Supported Cooperative Work and Social Computing | Sep 2021
   
   

6. Movie box office prediction based on ensemble learning
   Shuangyan Wu, Yufan Zheng, Zhikang Lai, Fujian Wu, Choujun Zhan
   IEEE Symposium on Product Compliance Engineering - Asia (ISPCE-CN) | Oct 2019 | Oral Presentation
   
   

Experience

1. Dec. 2022 - Jul. 2024, Research Assistant, Department of Electrical Engineering, City University of Hong Kong, China
2. Jun. 2022 - Nov. 2022, Algorithm technician, Industrial Software Development Division, Huangpu Institute of Materials, China
3. Mar. 2022 - Jun. 2022, Intern, Industrial Software Development Division, Huangpu Institute of Materials, China
4. Mar. 2019 - Mar. 2022, Research Assistant, Research Institute of Big Data and Artificial Intelligence (RIBDAI), Nanfang College of Sun Yat-sen University in Guangzhou, China

Service

Reviewer:

1. Internet of Things
2. Infectious Disease Modelling
3. IEEE Transactions on Consumer Electronics
4. Big Data Research

Talk:

1. Oct 2019, "Movie box office prediction based on ensemble learning" at ISPCE-CN 2019

Award

1. 2020 - 2021, Oustanding Graduates of NanFang College of Sun Yat-Sen University
2. 2019 - 2020, National Scholarship, China
3. Oct 2019, Merit award conference paper in 2019 IEEE International Symposium on Product Compliance Engineering-Asia

Project

1. Co-Investigator, 2020 - 2021, "E-business strategy mining based on big data and machine learning", Provincial College Students' Innovative Entrepreneurial Training Plan Program, China (10,000 CNY, No. S201912619030X)
2. Co-Investigator, 2019 - 2020, "Solar radiation estimation system based on hours of sunshine and Planck's law", Provincial College Students' Innovative Entrepreneurial Training Plan Program, China (10,000 CNY, No. S202012619022)
3. Principal Investigator, 2019 - 2020, "Box office forecasting based on big data and deep learning", Provincial College Students' Innovative Entrepreneurial Training Plan Program, China (10,000 CNY, No. S202012619021)