RESEARCH

RESEARCH INTERESTS

My research lies at the intersection of machine learning and mathematical epidemiology of health data science, biostatistics, computational biology, and statistical and mathematical modelling. Over the years, I have developed and applied quantitative frameworks that integrate mechanistic modelling with data-driven approaches to address complex public health challenges, particularly associated with emerging and re-emerging infectious diseases.

Application Areas:

• Time series forecasting, Epidemic trajectory prediction, Outbreak risk assessment, Markov Chain Monte Carlo, Parameter estimation and model calibration, Uncertainty quantification, Supervised and unsupervised learning, Real-world data analysis and visualization, Disease transmission dynamics, Numerical Analysis.

• Immunological data analysis, Within-host dynamics model, Early warning systems, Epidemiological risk mapping, Immune response modeling, Assessing outbreak risk and transmission patterns, Enhancing global disease surveillance and preparedness.

Current PhD Student

• Abhishek Kumar Dubey (Jan 2026 - Present)

Professional service: Reviewer for journals

1. Applied Mathematics and Computation

2. PLOS Neglected Tropical Diseases

3. Nonlinear Dynamics

4. Scientific Report

5. BMJ Open

6. Nonlinear Analysis Modelling and Control

7. Journal of Applied Mathematics and Computing

My research profile at Google Scholar and  ResearchGate