I am a computational & systems biologist and a biophysicist investigating the function and dynamics of biological systems using computational and experimental techniques. My research lies at the intersection of systems biology, immunology, data science, and biophysics. I employ mathematical modeling, computational simulations, analysis of biological and healthcare data, machine learning, and in vitro biophysical assays and molecular immunology techniques to understand how complex biological systems function and adapt with time.
Currently, I am working on immunological synapses with Prof. Michael L. Dustin at the Kennedy Institute of Rheumatology, University of Oxford. Previously, I worked on mathematical modeling of antibody responses in germinal centers, SARS-CoV-2 pandemic spread, and neuroinflammation as a postdoctoral research scientist in the Department of Systems Immunology at the Helmholtz Centre for Infection Research, Braunschweig, Germany, under the supervision of Prof. Michael Meyer-Hermann. I earned my Ph.D. from the Homi Bhabha National Institute, Mumbai, India, following my doctoral research on the emergence of memory and learning in intra- and inter-cellular networks at the Institute of Mathematical Sciences, Chennai, India, under the guidance of Prof. Sitabhra Sinha.
Methodologically, my past research primarily focused on developing computational models to understand emergent properties in complex biological systems. Currently, I am combining quantitative models with biophysical experiments at Oxford to study molecular interactions in immunological synapses between immune cells, aiming to unravel their activation and tolerance mechanisms to aid the development of next-generation therapeutics.
My research areas include intra-cellular signaling, molecular immunology, mathematical modeling of immune responses, and theoretical neuro-immunology. I am particularly interested in:
Emergence of T Cell microcluster and signaling during immune synapse formation in response to antigens (self- and non-self) and modern biologics (e.g., bispecific and trispecific T cell engagers).
Emergence of memory and learning in intra-cellular signaling networks, and their impact in sensing environmental cues.
Maintenance of self-tolerance in immune and nervous systems, and its breakdown in autoimmune and neuroinflammatory diseases.
Extrafollicular and germinal center response following infection and immunization, and emergence of autoimmunity.
Stochastic exclusion processes and their application in biology (e.g., in cellular transport).
Circadian regulation of neuro-immune interactions.
During SARS-CoV-2 pandemic, my key contribution to public health includes development of an adaptive method based on daily incoming data to determine the time evolution of reproduction numbers (Rt) and pandemic severity using a novel SARS-CoV-2-specific compartmental model integrated with healthcare usage. We used several variants of the model to help policy decisions globally, understand the high seroprevalence in hotspots (e.g., European ski resorts), and propose ways to minimize economic loss and death rates. Additionally, we explained why different methods for Rt estimation yield distinct results, underscoring the importance of interpreting pandemic data in conjunction with the overall number of cases and hospitalizations.
