Hello there! I am Mutong LIU (刘牧潼), a Ph.D. candidate in the Department of Computer Science at Hong Kong Baptist University, supervised by Prof. Yang LIU and co-supervised by Prof. Jiming LIU. My current research mainly focuses on Artificial Intelligence at Public Health, specifically developing and leveraging methodology in machine learning (ML) and reinforcement learning (RL) combined with epidemiological modeling to assess, predict, and control infectious diseases risk. I also maintain a broad interest in methodology development of multi-agent RL and spatiotemporal analytics.
My work aims to solve complex real-world problems such as infectious disease transmission risk assessment, epidemic risk prediction, effective resource allocation, and adaptive intervention strategy learning. My research spans AI/ML methodology development and application deployment in the context of infectious disease dynamics:
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Assessment of infectious disease risk and inference of transmission patterns:
Malaria risk Intensity Assessment (IDM’23) · TransCode (IDP’23) -
ML for Epidemic Dynamics Prediction:
Survey on ML for Infectious Disease Risk Prediction (ACM CSUR’25) · EpiDL (CIKM’23) -
ML & RL for Infectious Disease Control:
Empowering Epidemic Response (WI‑IAT’25) · Optimal Resource Allocation (IDP’22) -
Learning effective coordination in cooperative Multi-agent RL:
Probing Diametric Coordination Graphs for Multi-Agent Reinforcement Learning [Under Review]
Email address: csmtliu@comp.hkbu.edu.hk (Academic) / gigg0@icloud.com (Personal)
Research Interests
- Machine Learning, Reinforcement Learning, Spatiotemporal Analytics, Epidemic Prediction, Infectious Disease Modeling and Control
Education and Academic Qualification
| Period | Degree | Major |
|---|---|---|
| Jan.2021 - Present | PhD Candidate in Computer Science, Hong Kong Baptist University, Hong Kong, China | Computer Science |
| Sept.2016 - Jul. 2020 | B.E. in Network Engineering, Southwest University, Chongqing, China | Network Engineering |
| Sept.2015 - Jul. 2016 | Student in Plant Protection Faculty, Southwest University, Chongqing, China | Plant Protection |
Publications (Google Scholar)
Published:
- Mutong, Liu, Yang Liu, and Jiming Liu (2025). Empowering Epidemic Response: The Role of Reinforcement Learning in Infectious Disease Control. Accepted by the 2025 IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). [paper]
- Mutong Liu, Yang Liu, and Jiming Liu (2025). Machine Learning for Infectious Disease Risk Prediction: A Survey. ACM Computing Survey, 57(8), Article 212 (August 2025). https://doi.org/10.1145/3719663. [paper] [supplementary]
- Mutong Liu, Yang Liu, Jiming Liu (2023). Epidemiology-aware Deep Learning for Infectious Disease Dynamics Prediction. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM ‘23). [poster] [code][paper]
- Mutong Liu, Yang Liu, Ly Po, Shang Xia, Rekol Huy, Xiao-Nong Zhou, and Jiming Liu. (2023). Assessing the spatiotemporal malaria transmission intensity with heterogeneous risk factors: A modeling study in Cambodia. Infectious Disease Modelling, 8(1), 253-269. [paper]
- Jinfu Ren*, Mutong Liu*, Yang Liu, and Jiming Liu (2022). Optimal resource allocation with spatiotemporal transmission discovery for effective disease control. Infectious diseases of poverty, 11(1), 1-11. [paper]
- Jinfu Ren, Mutong Liu, Yang Liu, and Jiming Liu (2023). TransCode: Uncovering COVID-19 transmission patterns via deep learning. Infectious Diseases of Poverty, 12(1), 1-20. [paper]
- Li Tao, Mutong Liu, Zili Zhang, and Liang Luo (2022). Identifying multiple influential spreaders in complex networks by considering the dispersion of nodes. Frontiers in Physics, 9, 766615. [paper]
Under Review:
- Mutong Liu, Tiantian He, Yang Liu, Jiming Liu, and Yew-Soon Ong (2026). Probing Diametric Coordination Graphs for Multi-Agent Reinforcement Learning.
* Co-first author (Contributed equally).