RESEARCH
Research Interests
- Quantitative Biology
- Computational Modeling and Biophysics.
- Complex Systems
- Nonlinear and Stochastic Dynamics.
- Neural Excitability and Systems Neuroscience.
- Calcium Signaling.
- T Cell Dynamics and Cell Migration.
- Artificial Neural Networks.
Statement of Research Interests
I have a broad background in mathematical and computational biology, with proficiency in key research areas that lie at the interface of
complex systems, nonlinear and stochastic dynamics, biophysics, numerical computations and artificial intelligence. I use this expertise
to study quantitatively and mechanistically the underlying dynamics of various physiological systems in neuroscience, immunology and cell
biology. In collaborations with leading experimental scientists, my research group develops multiscale complex systems and computational
AI-based models to study the (sub)cellular and network dynamics of neurons, immune cells and motile cells; that includes:
- analyzing neural rhythms and the role of ion channels in regulating neural excitability,
- characterizing neural responses at the system level during rest and upon receiving a stimulus,
- studying spontaneous and evoked calcium responses in different cellular systems including neurons,
- deciphering ion channel kinetics,
- investigating how T cells are activated by pMHC-coated nanoparticles and how they respond as a population during diseases,
- unravelling how protein networks regulate cellular migration patterns.
These models adhere very closely to the physiological properties of each system under consideration, bridging its multiscale components and
predicting its emergent behaviour. The models are then used to generate testable predictions, explore how these systems are regulated
individually and collectively, how they evolve in time and how they respond to perturbations. Our experimental collaborators rely profoundly
on our work to understand their respective biological systems and our predictions and insightful conclusions drawn from our models
help steer their experimental work in new directions.