Mathematician specialising in delay systems, multi-scale epidemiological modelling, and data-driven disease policy.

Dr Gabor Kiss leads research at the interface of applied mathematics, infectious disease dynamics and public health decision support. His work centres on the analysis of multi-scale dynamical systems, particularly delay differential equations, nonlinear feedback processes and time-aggregation effects in biological systems. He has contributed to theory and application in slow–fast structure, delay-driven stability transitions and temporal regulatory behaviour in epidemiological and immunological systems.

A major strand of his research applies these analytical approaches to tuberculosis (TB), with emphasis on spatial heterogeneity, persistence mechanisms and intervention optimisation. Dr Kiss co-leads an international collaboration with Thailand’s Ministry of Public Health and King Mongkut’s University of Technology Thonburi, formalised through partnership letters from the Division of Tuberculosis. This programme provides access to sub-national surveillance data, enabling mathematical and statistical modelling to address strategic policy questions on elimination pathways, surveillance performance and the cost-effectiveness of control strategies.

In parallel, he leads modelling work on antimicrobial resistance (AMR), focusing on conditional resistance structure and hospital-level surveillance. His collaboration with Vietnam’s National Hospital of Tropical Diseases and the Hanoi University of Public Health explores probabilistic and network-based representations of co-resistance in Klebsiella pneumoniae. These studies link mathematical insight with laboratory-generated susceptibility data to quantify therapeutic separation, co-selection pressure and stewardship implications in resource-limited settings.

Taken together, these research strands form a coherent programme connecting dynamical systems theory, infectious disease modelling and real-world health system intelligence. His work bridges deterministic and stochastic models with operational surveillance analysis to support national decision-making frameworks.

Research Interests

• Delay differential systems and stability in feedback-regulated processes
• Multi-scale modelling and slow–fast structure
• Surveillance completeness, missingness dynamics and detection efficiency
• TB transmission modelling and elimination planning
• AMR resistance structure and hospital stewardship modelling
• Mathematical modelling as policy-enabling infrastructure

His research vision is to develop an integrated modelling platform for TB and AMR surveillance in Southeast Asia, combining mechanistic models, statistical inference and optimisation of intervention strategies. This programme links academic mathematics with public health agencies, providing a foundation for capacity building, international collaboration and long-term partnership between modelling communities and health ministries.