Interview with Prof. Sarika Jalan

  1. Brief self-introduction

This is Sarika Jalan from IIT Indore. Currently, I am at Physics of Complex Systems @ IBS for my sabbatical. Broad areas of my research are complex networks including social networks, synchronization, spatio-temporal chaos, spectral graph theory and applications of RMT.

  1. Could you explain your recent research?

Recently, we have been interested in understanding how dynamical properties of nonlinear units coupled through a network can be controlled or tuned by multiplexing this network with another network forming a multilayer network.  Remarkably, we have found that by appropriate multiplexing one can induce first order phase transition to synchronization, referred as explosive synchronization, in networks which are incapable to exhibit the same in isolation.

  1. What is your future research plan?

To relate structural properties of the underlying network structure with dynamical properties, such as cluster synchronization and explosive synchronization. I have two immediate future goals: The first one, which is more mathematically inclined, aims to relate localization properties of underlying adjacency matrices with the complexity of corresponding networks. Second one is of more interdisciplinary in nature combining machine learning techniques to achieve the goal of relating network structure representing a complex system with dynamical properties of that complex system.

  1. What motivated you to research with IBS, and what is the current research in IBS?

IBS has a vibrant international atmosphere with a great scope of inter-disciplinary research and stimulating discussions. The physics of complex systems (PCS) group has scientists with expertise in Anderson localization, and being in IBS offers a unique opportunity for advancing my research on localization properties of complex networks.

The second part of my work which pertains to machine learning applications aiming to relate network structure with dynamical properties of corresponding complex systems is being carried out in collaboration with the data science center at IBS. As a first step, we have initiated a collaborative project on “Twitter networks” by utilizing COVID19 data.

  1. What are the most challenging and favorite parts of your researches?

Networks provide a very simple framework to model and predict various emerging properties of a diverse range of real-world complex systems. The real challenge, also the favourite part of my research, is to identify the crucial properties of an individual complex system and incorporate them in the corresponding “coupled dynamics on networks” model for a better understanding and predictions of the system’s behaviours. Interestingly, a variety of complex systems having underlying network structures exhibit universal features and mechanisms making this direction of research extremely fascinating.

  • Contact: sarika (at)