This page showcases my research in computational biology, focusing on the development of models and simulations to understand biological behavior at cellular or systems level and how it contributes towards health and/or disease.
My work ranges from visualizing biological-circuits regulating gene expression, to how diverse cells interact spatially over time. These efforts for instance help explain (1) why B-cells from immunocompromised patients fail to produce effective levels of antibodies, (2) how does the immune system responds to a viral-infection in a cancer patient, (3) how cancer cells escape a particular therapy, and (4) how to design effective therapies that allow tumor eradication. Each project integrates biological data with computational frameworks to generate predictive insights that inform experimental design and clinical applications.
Gene regulatory network of antibody folding in B-cells
2021, Clinical & Experimental Immunology
Platform: BioTapestry
A systematic analysis on the clinical safety and efficacy of onco-virotherapy

Modelling virotherapy in presence of resistant cells
2022, PLOS Computational Biology
GitHub: Oncolytic Virus Resistance simulation
A systematic analysis on the clinical safety and efficacy of onco-virotherapyModelling immune response to virotherapy
2024, Scientific reports
A systematic analysis on the clinical safety and efficacy of onco-virotherapy

Modeling therapy design to overcome resistance
2025, BioRxiv
A systematic analysis on the clinical safety and efficacy of onco-virotherapyMultiplex ELISpot to study anti-CMV T cells
2025, MedRxiv
A systematic analysis on the clinical safety and efficacy of onco-virotherapy