3
First-author work
Academic homepage
Hong Liu
Infectious Disease Forecasting Spatiotemporal Dynamics Viral Evolution
I have graduated from Macau University of Science and Technology with an M.Sc. in Computer Science and Technology. I will return to Xiamen University to continue doctoral study in Epidemiology and Health Statistics, building on work in infectious disease forecasting, influenza co-circulation analysis, outbreak modelling, and the integration of epidemic dynamics with viral evolution.
Current work links multimodal forecasting, epidemic dynamics, and interpretable analytical workflows, with longer-term research extending toward viral evolution and early-warning systems.
Research evidence
A concise evidence band keeps the first screen anchored in outputs rather than ornament.
7
Published papers
8
Public repositories
Profiles and quick routes
Academic identity
Latest Degree
Macau University of Science and Technology
M.Sc. in Computer Science and Technology, Faculty of Innovation Engineering
Full scholarship and living allowance; supervised by Academician Nanshan Zhong and Prof. Chitin Hon
Co-supervised by Prof. Tianmu Chen (Xiamen University)
Next Step
Xiamen University
Returning for doctoral study in Epidemiology and Health Statistics, School of Public Health
Supervised by Prof. Tianmu Chen
Undergraduate
Xiamen University
B.Med. in Preventive Medicine, School of Public Health
Supervised by Prof. Tianmu Chen
B.Econ. in Statistics, Wang Yanan Institute for Studies in Economics (WISE)
Selected research outputs
Representative first-author and lead work appears first so the homepage communicates research direction and evidence before secondary context.
3
First-author studies
7
Published papers
8
Public repositories
2025 · First author
Multi-modal Adaptive Estimation for Temporal Respiratory Disease Outbreak
First-author MAESTRO study. In the documented evaluation context, the reported R² reached 0.956 on a 10-year Hong Kong influenza dataset.
2025 · First author
Dual-Model Framework for CHIKV Transmission Modeling: ODE and Petri Net Analysis of the 2025 Foshan Outbreak
First-author dual-framework outbreak modelling study for the 2025 Foshan chikungunya outbreak.
2026 · First author
Spatiotemporal instability of influenza seasonality during viral co-circulation
First-author npj Systems Biology and Applications article. Accepted on 17 April 2026 and published online on 04 May 2026.
Research focus
Current work is organized around a compact set of research themes rather than a long inventory of activities.
Infectious disease forecasting and early warning
Recent M.Sc. work centered on multimodal forecasting, non-stationary time-series analysis, and early-warning-oriented modelling for infectious diseases, especially respiratory disease activity and influenza-related scenarios.
Influenza co-circulation and spatiotemporal dynamics
A central line of work studies co-circulation patterns, synchronous and lagged relationships, and feature extraction for influenza-related signals in China, using interpretable time-series and multiscale analytical methods.
Small-sample outbreak modelling
Recent work on the 2025 Foshan chikungunya outbreak combines ODE and Petri Net formulations to compare transmission interpretation, intervention effects, and uncertainty under small-sample conditions.
Epidemic dynamics and viral evolution
My broader research narrative links macroscopic epidemic patterns with microscopic viral evolution, and the longer-term agenda extends toward connecting epidemiological signals, phylodynamic evidence, and future early-warning models within a coherent framework.
Current snapshot
A concise summary of the current research stage, active methods, and outward-facing profile links.
My completed M.Sc. and continuing doctoral trajectory includes MAESTRO for multimodal respiratory disease forecasting, influenza co-circulation and co-infection analysis, dual-framework ODE/Petri Net modelling for chikungunya transmission, and ongoing maintenance of an infectious-disease intelligence platform for data collection and analytical support. The broader narrative focuses on non-stationary time-series analysis, small-sample outbreak dynamics, and linking macroscopic epidemic patterns with microscopic viral evolution in future early-warning systems. I aim to continuously integrate epidemiological signals with phylodynamic evidence to provide reliable, multi-scale insights for public health preparedness and decision-making.
Infectious disease forecastingEarly warningInfluenza co-circulationODE / Petri Net modellingMultimodal data fusionViral evolution
Research software and analytical systems
Software artifacts are presented as supporting evidence for modelling, forecasting, data engineering, and research workflows.
research code
MAESTRO
Multimodal forecasting framework for respiratory disease activity and early-warning-oriented time-series analysis.
Research framework connecting multimodal respiratory disease forecasting with documented evaluation and paper output.
ForecastingEarly warningMultimodal modellingTime series
research code
ODE-Petri-Chikungunya
Research workflow comparing ODE and Petri Net perspectives for the 2025 Foshan chikungunya outbreak.
Dual-model outbreak analysis workflow linking mechanistic interpretation, intervention phases, and manuscript development.
Mechanistic modellingODEPetri NetOutbreak analysis
platform
Infectious disease intelligence platform
Crawler, database, ETL, and visualization workflow for infectious-disease news collection, monitoring, and research-oriented data support.
Operational data pipeline for infectious-disease intelligence, from collection and cleaning to monitoring-oriented visualization.
ETLCrawlerDatabaseVisualization
software
bibverify
BibTeX validation and metadata completion tool for DOI, author, year, deduplication, and citation normalization workflows.
Utility for reference verification, metadata completion, deduplication, and citation cleanup across writing workflows.
Bibliographic toolingDOI validationMetadata completion
Selected highlights
Short evidence-led notes reinforce the main outputs without repeating the entire homepage narrative.
Developed the MAESTRO multimodal forecasting framework for respiratory disease activity; in the documented evaluation context, the reported R² reached 0.956 on a 10-year Hong Kong influenza dataset.
Built an ODE and Petri Net dual-model workflow for the 2025 Foshan chikungunya outbreak to compare intervention phases, transmission indicators, and sensitivity under small-sample conditions.
Designed an analytical pipeline for influenza co-circulation and co-infection signals, leveraging interpretable time-series decomposition and multiscale frequency-domain coupling patterns.
Independently developed and continuously maintained an infectious-disease news collection, database, and visualization platform that supports research-oriented data acquisition and monitoring workflows.
Navigate the site
Use the sections below for fuller research themes, publication records, CV material, and project context.