Music: I am interested in applying data analysis and statistical methods to study the characteristics of Rāgas in Indian classical music, with a particular focus on Carnatic music. A key requirement for such work is the availability of reliable data. Fortunately, the Indian music tradition offers rich resources in the form of audio recordings, written notations, and, importantly, well-preserved oral lineages. These paramparās have safeguarded compositions across generations, maintaining a living continuity with musical practices that extend back nearly three centuries.

Drawing on these diverse sources, I investigate questions related to the internal structure of Rāgas, their melodic trajectories, and the nature of transitions within and between them.

Statistical physics: During my PhD, we developed a novel Monte Carlo algorithm alongside an analytical formalism to study rare events in aggregation — a fundamentally non-equilibrium and irreversible stochastic process [see publications]. The central object used to characterise such rare events is the large deviation function, which is typically very difficult to compute analytically.

Using a Doi–Peliti–based field-theoretic framework that we developed, we were able to derive the full large deviation function and the corresponding instanton trajectories for the constant, sum, and product kernels. This allowed us to obtain an exact characterisation of fluctuation behaviour beyond typical events.

My current work extends these ideas to more complex settings, where aggregation competes with additional processes such as fragmentation or external input, leading to richer non-equilibrium dynamics.

Publications