research

I study how noise, coupling, and nonlinearity shape complex systems, and how these dynamics can support computation, inference, and control. My approach brings analytical and numerical models into contact with experimental data and physical implementations.

Cortical dynamics and modelling from data

At CNRS/FEMTO-ST, I worked with Dr Jean-Julien Aucouturier’s group on the dynamics of sleep onset. Our 2026 paper develops a stochastic model of switching between wake and sleep states and a procedure for fitting its parameters to individual EEG recordings. The work connects dynamical models with variability observed in biological data.

Learning the bistable cortical dynamics of the sleep-onset period · Code and data

Synchronization and control of coupled systems

My work at IIT Bombay explored how changing interactions and oscillator frequencies can regulate collective dynamics. In our study of frequency shuffling, repeatedly exchanging frequencies among oscillators allowed synchronization to occur at lower coupling strengths. We tested the idea analytically and with electronic oscillator experiments.

Synchronization through frequency shuffling · Regulating dynamics through intermittent interactions

Noise-assisted physical computing

During my PhD at IISER Mohali with Prof. Sudeshna Sinha, I investigated how noise and nonlinearity in bistable systems can implement logical operations. Subsequent work explored logic through synchronization, memristive circuits, and invertible logic in coupled nonlinear systems, with numerical models and circuit experiments.

Noise-aided invertible logic from coupled nonlinear systems · Emergent noise-aided logic through synchronization

Transient dynamics and heteroclinic networks

At Constructor University Bremen with Prof. Hildegard Meyer-Ortmanns, I studied heteroclinic dynamics as a framework for transient processes, including their relaxation and potential computational applications.

On relaxation times of heteroclinic dynamics

Methods

• Scientific computing and dynamical systems modelling in Python and MATLAB, using NumPy, SciPy, Matplotlib, pandas, and NetworkX.
• System identification and reduced-order modelling with SINDy, HAVOK, and SHRED.
• Design and characterization of nonlinear electronic circuits, experimental automation, and data acquisition.
• Experiments with coupled electronic and flame oscillators.

See the complete publication list and CV.