30th Seminar

Study of interactions in complex systems

Dr. Subhradeep Roy
Embry-Riddle Aeronautical University, Daytona Beach Campus, USA

Complex systems consist of many interacting components, which work in unison to accomplish a task. Animal collective behavior, the human brain, social networks, and transportation networks are a few examples of complex systems. I will demonstrate my approach to study complex systems using both analytical and experimental techniques to meet the three broad objectives:
(1) understanding the nature of interactions in real-world systems, ranging from wild bat pairs in motion to interaction among car drivers in traffic,
(2) developing techniques for quantitative analysis of real-world dataset to learn the features of such interactions, and
(3) building robust systems using analytical frameworks by adapting lessons from the real-world biological systems.
Specifically, I will present how data-driven approaches can be applied to characterize interactions with applications in traffic. I will demonstrate how research findings on pairwise interactions in bats can be used to learn about group-level behavior using agent-based models.

Speaker Bio
Dr. Subhradeep Roy received his Bachelor's and Master's degrees in Mechanical Engineering from the Indian Institute of Engineering Science and Technology, Shibpur in 2010 and the Indian Institute of Technology Kanpur in 2012, respectively, and a Ph.D. in Engineering Mechanics from Virginia Tech in 2017. From 2017-2019 he was a post-doctoral scholar in the Physical Computing Laboratory at Virginia Tech. From 2019-2021, he held a tenure-track assistant professor position in the Mechanical Engineering Department at California State University, Northridge. In Fall 2021, he joined the Mechanical Engineering Department at Embry-Riddle Aeronautical University - Daytona Beach campus, where he is currently a tenure-track assistant professor. His research interest is to study dynamical systems emerging from the natural world using an interdisciplinary approach and by collaborating with researchers from various disciplines. He directs the 'Complex Dynamical Systems Laboratory' and works on various topics, including bat swarms to vehicular traffic.

29th Seminar

Speed limits on the local stability of classical dynamical systems

Dr. Swetamber Das
University of Massachusetts, USA

Uncertainty relations are a prominent feature of quantum mechanics. However, classical systems are also characterized by a type of uncertainty – deterministic chaos – in which the uncertainty in their initial conditions leads to unpredictable behavior. In this presentation, I will discuss our theory of dynamical systems that mirrors the density matrix formulation of quantum mechanics. Central to this formalism is a classical density matrix, with dynamics governed by a von Neumann-like equation of motion. and dynamical observables, such as Lyapunov exponents, that evolve in time under an Ehrenfest-like theorem. Leveraging this formalism, we derive a family of speed limits on observables in the tangent space that are set by the local dynamical (in)stability. These classical speed limits are mechanical in nature and obtained from a Fisher information constructed in terms of Lyapunov v ectors and the local stability matrix. For a dynamical system with a time-independent local stability matrix, these speed limits reduce to a classical analog of the Mandelstam-Tamm time-energy uncertainty relation in quantum mechanics. Our analytical and numerical results for model systems show this theory applies to arbitrary deterministic systems including those that are conservative, dissipative and driven.

Speaker Bio
Dr. Swetamber Das completed his PhD in Physics from IIT Madras and is currently a post-doc at the University of Massachusetts, Boston. Prior to his current position, he has been a visiting scientist at the Max Planck Institute in Dresden.

28th Seminar

The science of modelling infectious disease outbreaks

Dr. Rachel Slayton
Center for Disease Control and Prevention (CDC), USA

Epidemiological modeling of infectious disease transmission informs public health decision-making by providing a way to synthesize data from multiple data sources, adjust for potential biases, forecast the trajectory, evaluate the impact of interventions, and conduct sensitivity analyses. We often adapt methods from the physical sciences, with compartmental models comprised of ordinary differential equations serving a central role in modeling of emerging infectious diseases. Network models also provide important insights about optimizing public health prevention strategies (e.g., including evaluation of targeted prevention strategies focused on influential nodes) for infectious diseases, including Coronavirus Disease 2019 (COVID-19). Using a variety of analytic approaches, we have modeled transmissions among individuals within healthcare facilities, (e.g., nursing homes) to assess the relative value of different testing and mitigation strategies, including comparing the impact of testing strategies focused on either nursing home residents or healthcare providers.

Speaker Bio
Dr. Slayton leads a mathematical modeling unit focused on infections and multi-drug resistant organisms in the CDC’s Division of Healthcare Quality Promotion, Epidemiology Research and Innovations Branch. She is the Scientific Director for the Modeling Infectious Diseases in Healthcare network and has co-lead CDC’s COVID-19 mathematical modeling unit.

27th Seminar

Complexity science approach to social progress and sustainability development

Prof. Anirban Chakraborti
BML Munjal University

There is no consensus on what complexity science is; for many, it is an interdisciplinary field that studies “complex systems”, using a plethora of tools and techniques based in physics, mathematics, statistics, and computer science to deal with questions that are amenable to these techniques in various domains such as environment, biology, sociology, economics, etc. Typically, a complex system is composed of parts that interact on multiple time and length scales, which include examples such as ant colonies, brain, the climate, and the society. Social progress and sustainability development deal with complex issues, which often require a holistic approach. We would like to discuss these issues in the context of complexity science.

Speaker Bio
Anirban Chakraborti is a Professor at the School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi. Earlier, he had worked as an Associate Professor at the Chair of Quantitative Finance, École Centrale Paris, France, and as a Lecturer in Theoretical Physics, Banaras Hindu University, Varanasi. He obtained a Ph.D. in Physics from Saha Institute of Nuclear Physics, India and later completed the Habilitation (HDR) in Physics from Université Pierre et Marie Curie (Paris VI), France. He has more than two decades of experience as a scientist, working in many reputed universities and research institutions in India, Europe, Japan, and USA. He was awarded the prestigious Young Scientist Medal of the Indian National Science Academy in 2009. His main research interests lie in the areas of Econophysics, Sociophysics, Data Science, Complex Systems, Statistical Physics, Quantum Physics and Nanomaterial Science.

26th Seminar
Analysis of models of superfluidity

Superfluidity is of tremendous interest in condensed matter physics and more recently, in engineering too. At non-zero temperatures, the superfluid and normal fluid (of Helium) interact with each other. After a brief introduction to the physics of the problem, we will consider a macro-scale and a micro-scale model, both of which describe the coupled dynamics of the two fluids. Mathematical analysis concerning the existence, regularity and uniqueness of solutions to these models will be presented. Among other things, the notion of weak-strong uniqueness will be relaxed to include "moderate" or less-regular strong solutions. All the results constitute joint work with Konstantina Trivisa (University of Maryland College Park).

Speaker Bio
Pranav obtained a Dual Degree in Mechanical Engineering (with a focus on Thermal Engineering, and a minor in Physics) from IIT Madras in 2016. During his undergraduate studies, he spent a summer as a research intern at the Karlsruhe Institute of Technology in Germany.

He attended the University of Maryland for graduate school, getting his Masters and Doctoral degrees in Physics in 2019 and 2022. Next month, he will join the University of Southern California as a postdoc in the Department of Mathematics.

25th Seminar

Investigating neural correlates of inhibitory control: How do we stop ourselves?

Dr. Vignesh Muralidharan
Aronlab of Cognitive Neuroscience, University of California San Diego, USA

In everyday life, we encounter situations where we need to control our actions, urges, thoughts, and emotions to achieve both short and long-term goals. For instance, one would have to control the urge to eat junk food while on a diet. One such form of executive control, referred to as inhibitory control, is the ability to stop or suppress unwanted actions and provocations from occurring, especially in situations where there is a strong pull toward them. There are different contexts where this form of control might be needed. In some scenarios, one might have to stop already initiated actions in reaction to external cues (reactive control), thus driving top-down control processes, e.g., stopping yourselves from stepping onto the street when you see a car rushing towards you. In other cases, one might have to prepare in advance to set up mental states that can aid in stopping (proactive control), e.g., stopping anxious thoughts before an important exam. Multiple lines of evidence have shown that such forms of inhibitory control involve brain networks that include prefrontal, basal ganglia, and sensorimotor regions. In my talk, I will outline the ways in which we probed the neural correlates of control in these brain regions as people attempted to stop initiated actions or induced brain states that aid stopping. I will also explain how our findings using high temporal resolution electrophysiology, functional brain stimulation, and computational modeling approaches revealed the dynamics of these regions and the role of specific oscillatory (beta-band) rhythms while people exert these forms of control. I will finally discuss how these findings form the precursors for future research aimed at developing strategies that can aid people’s ability to control their actions and thoughts. This could potentially lead to applications that target behavioral deficits in impulse-control disorders like Parkinson’s disease, Tourette’s syndrome, obsessive-compulsive disorder, and anxiety-related disorders.

Speaker Bio
Vignesh Muralidharan, is a cognitive and computational neuroscientist with expertise in the domain of human cognitive and motor control. He did his Ph.D. at the Indian Institute of Technology Madras under the guidance of Prof. Srinivasa Chakravarthy where he worked on conceptualizing and building brain-inspired computational models to explain gait control in normal people and its deficits in Parkinson’s disease, a brain disorder. His doctoral experience piqued his interest in understanding the influence of top-down cognitive processes on our actions. He subsequently did his post-doctoral training at the Department of Psychology, University of California San Diego with Prof. Adam Aron, where he has been studying how humans override inappropriate responses and impulses and the brain mechanisms underlying them. His research involves designing tasks mimicking real-world scenarios of control in the lab and gaining insights into the mechanisms of cognitive control by looking at brain activity and functionally stimulating brain areas while people perform these tasks. His passion is to further the understanding of human self-control and develop neurotechnology applications that can aid or enhance cognitive control abilities.

LIVE link to talk 

24th Seminar

Synchrony as constraint

Prof. Ramakrishna Ramaswamy
Indian Institute of Technology Delhi

We obtain necessary conditions for the {\em generalised
synchronization} of coupled dynamical systems, namely the process of confining the dynamics to lower dimensional submanifolds in the phase space. In this framework, synchronization is seen as a process of imposing algebraic constraints which may also be time-dependent. We propose a procedure for constructing (non-unique) coupling functions that can guide the flow to the desired submanifold which can also be made stable and attracting. A geometric analysis of the stability of this manifold is provided, and the procedure is demonstrated through representative examples.

Speaker Bio
Prof Ram Ramaswamy obtained his B. Sc. in Chemistry (1972) from Loyola College, Chennai, M. Sc. in Chemistry from the IIT, Kanpur, and Ph.D. (1978) from Princeton University where he worked under the supervision of Herschel Rabitz. He then moved to California Institute of Technology, Pasadena where he was between 1978 and 1980, working with Prof. Rudolph A. Marcus. He returned to India in 1980 and joined the Tata Institute of Fundamental Research as Visiting Fellow (1981) and Fellow (1983). In 1986 he moved to the Jawaharlal Nehru University as one of the first members of the School of Physical Sciences. 

He spent a year on sabbatical at the Institute for Molecular Science in Okazaki, Japan (1989–90). A second sabbatical (2004–05) was spent at the Institute for Advanced Study, Princeton. In 2011 he was appointed Vice Chancellor of the University of Hyderabad. He resigned the position in January 2015, returning to his substantive positions at the Jawaharlal Nehru University. After his retirement from JNU in 2018, he joined IIT Delhi as visiting professor where is still serving.

He was Vice President of the Indian National Science Academy, New Delhi, as well as of the Indian Academy of Sciences, Bangalore. He served as President of the Indian Academy of Sciences, Bangalore, during 2016–2018.

Recorded Talk 

23rd Seminar

Dynamics of fluids around laser heated colloidal particles

Prof. Sutapa Roy
Indian Institute of Technology, Gandhinagar

Laser illuminating a Janus colloid which is suspended in a near-critical binary solvent leads to the formation of the concentration gradient and coarsening patterns around the colloid, which leads to the particle's phoretic motion. Using analytical theory and numerical simulations, we investigate this non-equilibrium phenomenon under the influence of a time-dependent temperature gradient. Our predictions are confirmed by experiments with Gold-capped Janus particles immersed in PnP-water binary liquid mixture. We also present results for particles kept confined in thin films. 

Speaker Bio
Sutapa Roy completed B.Sc with Physics honours from St. Xavier's College Kolkata (2003-2006), and M.Sc in Physics from the Indian Institute of Technology Madras (2006-2008). Following this, she obtained her Ph.D. from Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore (2008-2013), working in Statistical Physics. In 2014 she joined the Max-Planck Institute for Intelligent Systems, Stuttgart, Germany, as a Postdoctoral Researcher, where from 2015 she was employed as a Research Scientist.

Since December 2020 she is an Assistant Professor in the Physics discipline of Indian Institute of Technology Gandhinagar. Her research focuses on various soft condensed matter systems.

Link to talk (Recorded) 

22nd Seminar

Exact model reduction of nonlinear finite element models via spectral manifolds

Dr. Shobhit Jain
ETH Zurich, Switzerland 

Models of realistic nonlinear structures are characterized by very high dimensionality that renders full-system simulations infeasible. Despite the broad availability of dedicated software packages, the prediction and continuation of steady-state response in such systems remains a serious computational challenge for full-scale nonlinear finite element models. The recent theory of Spectral Submanifolds (SSM) has laid the foundation for a rigorous model reduction of such nonlinear systems, leading to reliable steady-state response predictions within feasible computation times. Further developments have made the direct computation of such invariant manifolds and their reduced dynamics scalable to realistic, nonlinear finite-element models.

In this talk, we survey the basics of SSM theory and show how SSMs can be used to achieve an exact model reduction for realistic finite-element models of complex systems. We also mention recent technical developments, and survey applications to modelling and prediction in structural vibrations using direct as well as data-driven methods.

Speaker Bio
Shobhit Jain received his B. Tech in Mechanical Engineering from IIT Roorkee (2011) before joining the Product and Technology Development Centre at Larsen & Toubro, Mumbai as a Senior Design Engineer (2011-2013). Thereafter, he received his Master of Science degrees in Mechanical Engineering and Applied Mathematics from Delft University of Technology, Netherlands (2015) followed by a Dr. Sc. from ETH Zurich, Switzerland (2016-2019). Currently, Shobhit is a postdoctoral fellow at the Chair in Nonlinear Dynamics, ETH Zurich (since 2019).

Dr. Jain performs research in the broad area of model reduction for nonlinear dynamical systems. His research focuses on the development of computational methods and mathematical software that enable modeling, analysis, and robust reduction of high-dimensional, nonlinear dynamical systems found in applied science and engineering. 

Link to talk (Recorded) 

21st Seminar

Stochastic control of ecological networks

Dr. Arnaud Z Dragicevic
INRAE France 

The aim of the following work is to model the maintenance of ecological networks in forest environments, built from bioreserves, patches and corridors, when these grids are subject to random processes such as extreme natural events. The management plan consists in providing both temporary and sustainable habitats to migratory species. It also aims at ensuring connectivity between the natural areas without interruption. After presenting the random graph-theoretic framework, we apply the stochastic optimal control to the graph dynamics. Our results show that the preservation of the network architecture cannot be achieved, under stochastic control, over the entire duration. It can only be accomplished, at the cost of sacrificing the links between the patches, by increasing usage of the control devices. This would have a negative effect on the species migration by causing congestion among the channels left at their disposal. The optimal scenario, in which the shadow price is at its lowest and all connections are well-preserved, occurs at half of the course, be it the only optimal stopping moment found on the stochastic optimal trajectories. The optimal forestry policy thus has to cut down the timing of the practices devoted to biodiversity protection by half.

Speaker Bio
 Dr. Arnaud Z. Dragicevic is a senior researcher in bioeconomics at INRAE -- the French National Research Institute for Agriculture, Food and Environment. He holds a Ph.D degree from École Polytechnique [IP Paris] and an Sc.D degree or Habilitation from the Aix-Marseille School of Economics [AMU]. His research interests include bioeconomics, socio-ecological systems and sustainability. The modeling tools he holds in high regard are the graph- and game-theoretic settings seen as governed by evolutionary dynamics.

Link to talk (recorded)


Complex Systems & Dynamics     Indian Institute of Technology Madras     Chennai 600036     India