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Saturday, 16 June 2018
Time Speaker Title Resources
09:00 to 10:30 Soumitro Banerjee (IISERK, India) Introduction to Dynamical Systems
10:30 to 11:00 -- Tea break
11:00 to 12:30 Soumitro Banerjee (IISERK, India) Introduction to Non-smooth Dynamical Systems
12:30 to 13:30 -- Lunch
13:30 to 15:30 Soumitro Banerjee (IISERK, India) Bifurcations in one-dimensional piecewise smooth continuous maps
15:30 to 17:00 Hemant Bhate (University of Pune, India) TBA
Sunday, 17 June 2018
Time Speaker Title Resources
09:00 to 10:30 Soumitro Banerjee (IISERK, India) Border-Collision Bifurcations in One-Dimensional Discontinuous Maps
10:30 to 11:00 -- Tea Break
11:00 to 12:30 Hemant Bhate (University of Pune, India) TBA
12:30 to 13:30 -- Lunch
13:30 to 15:30 Kuntal Mandal (NIT Sikkim, India) TBA
15:30 to 17:00 Soumitro Banerjee (IISERK, India) Bifurcations in 2D Piecewise Smooth maps
Monday, 18 June 2018
Time Speaker Title Resources
09:00 to 10:30 Soumitro Banerjee (IISERK, India) On the Stability of periodic orbits in switching dynamical systems
10:30 to 11:00 -- Tea Break
11:00 to 12:30 Viktor Avrutin (University of Stuttgart, Germany) Introductory Remarks
12:30 to 13:30 -- Lunch
Tuesday, 19 June 2018
Time Speaker Title Resources
09:00 to 10:30 David Simpson (Massey University, New Zealand) Dynamics and Bifurcations of piecewise - Smooth
10:30 to 11:00 -- Tea break
11:00 to 12:30 Viktor Avrutin (University of Stuttgart, Germany) Bifurcations of chaotic attractors
12:30 to 13:30 -- Lunch
13:30 to 15:30 Hemant Bhate (University of Pune, India) TBA
15:30 to 17:00 Viktor Avrutin (University of Stuttgart, Germany) Bifurcations of chaotic attractors (Lecture 2)
Wednesday, 20 June 2018
Time Speaker Title Resources
09:00 to 10:30 David Simpson (Massey University, New Zealand) TBA
10:30 to 11:00 -- Tea Break
11:00 to 12:30 Viktor Avrutin (University of Stuttgart, Germany) Bifurcations of chaotic attractors (Lecture 3)
12:30 to 13:30 -- Lunch
13:30 to 15:30 Viktor Avrutin (University of Stuttgart, Germany) TBA
15:30 to 17:00 David Simpson (Massey University, New Zealand) TBA
Thursday, 21 June 2018
Time Speaker Title Resources
09:00 to 10:30 Viktor Avrutin (University of Stuttgart, Germany) Adding Structures
10:30 to 11:00 -- Tea Break
11:00 to 12:30 David Simpson (Massey University, New Zealand) TBA
12:30 to 13:30 -- Lunch
13:30 to 15:30 David Simpson (Massey University, New Zealand) TBA
15:30 to 17:00 Viktor Avrutin (University of Stuttgart, Germany) TBA
Friday, 22 June 2018
Time Speaker Title Resources
09:00 to 10:30 Paul Glendinning (University of Manchester, UK) Dynamics of piecewise smooth maps (Lecture 1)
10:30 to 11:00 -- Tea break
11:00 to 12:30 -- Lunch
11:00 to 12:30 David Simpson (Massey University, New Zealand) TBA
13:30 to 15:30 Viktor Avrutin (University of Stuttgart, Germany) TBA
15:30 to 17:00 Paul Glendinning (University of Manchester, UK) Dynamics of piecewise smooth maps (Lecture 2)
Saturday, 23 June 2018
Time Speaker Title Resources
09:00 to 10:30 David Simpson (Massey University, New Zealand) TBA
10:30 to 11:00 -- Tea Break
11:00 to 12:30 Paul Glendinning (University of Manchester, UK) Dynamics of piecewise smooth maps (Lecture 3)
12:30 to 13:30 -- Lunch
13:30 to 15:30 Paul Glendinning (University of Manchester, UK) Dynamics of piecewise smooth maps (Lecture 4)
15:30 to 17:00 Soumitro Banerjee (IISERK, India) Switching dynamical systems
Sunday, 24 June 2018
Time Speaker Title Resources
09:00 to 10:30 Paul Glendinning (University of Manchester, UK) Dynamics of piecewise smooth maps (Lecture 5)
10:30 to 11:00 -- Tea Break
11:00 to 12:30 -- Discussion
12:30 to 13:30 -- Lunch
13:30 to 17:00 -- Break
Monday, 25 June 2018
Time Speaker Title Resources
09:00 to 10:30 Debabrata Biswas (Rampurhat College, India) TBA (Tutorial class Software)
Tuesday, 26 June 2018
Time Speaker Title Resources
09:30 to 10:00 -- Registration
10:00 to 10:15 -- Inauguration
10:15 to 11:00 Elena Surovyatkina (Potsdam institute of Climate research/Institute of Space Research, Moscow) Prediction of Indian summer monsoon: from Complex Network to Tipping elements approach
11:00 to 11:30 -- Tea
11:30 to 12:15 Rahul Pandit (IISc, India) Cardiac Arrhythmias: What can we learn from Mathematical Models for Cardiac Tissue?
12:15 to 14:00 -- Lunch
14:00 to 14:45 Arun Tangirala (IITM, India) Complex Networks in Difference Fields
14:45 to 15:30 David Simpson (Massey University, New Zealand) Fractal structures in multi-dimensional piecewise-linear maps
15:30 to 16:00 -- Tea
16:00 to 16:45 Karthik Raman (IITM, India) Learning and Predicting Novel Metabolic Pathways through subgraph mining
16:45 to 17:30 Paul Glendinning (University of Manchester, UK) Robust Chaos revisited

The idea of Robust Chaos was introduced by Banerjee, Grebogi and Yorke in the 1990s to describe systems with chaotic attractors on intervals of parameter values. I shall look at the various methods and results -- both theoretical and numerical -- available to investigate this phenomenon in piecewise smooth dynamical systems.

Wednesday, 27 June 2018
Time Speaker Title Resources
09:30 to 10:15 Sudeshna Sinha (IISERM, India) Dynamics of Rewired Network
10:15 to 11:00 Shashi Thutupalli (NCBS, India) Chimera states in mechanical oscillator networks
11:00 to 11:30 -- Tea
11:30 to 12:15 Abhishek Dhar (ICTS, India) Light-cone spreading of perturbations and the butterfly effect in classical spin chains
12:15 to 14:00 -- Lunch
14:00 to 14:45 Manish Shrimali (Central University of Rajasthan, India ) Explosive death in network of nonlinear oscillators
14:45 to 15:30 Karthik Raman (IITM, India) Enumerating All Possible Biosynthetic Pathways in Metabolic Networks
15:30 to 16:00 -- Tea
16:00 to 16:45 Arun Tangirala (IITM, India) Reconstructing Causal Networks from Data: Overview and Developments (Part 2)
16:45 to 17:30 Parongama Sen (University of Calcutta, India) Dynamical phenomena on networks: two specific problems
Thursday, 28 June 2018
Time Speaker Title Resources
09:30 to 10:15 Hemant Bhate (University of Pune, India) Galois theory for Schrier graphs: bounded automata, self similar graphs and zeta functions
10:15 to 11:00 G. Rangarajan (IISc, India) Sparse VAR and Network Representations of High Dimensional Time Series Data

Obtaining a sparse representation of high dimensional data is importan t since it provides an efficient representation of the data and facilitates its further analysis. Conventional Vector Autoregressive (VAR) modeling methods applied to such data result in non-sparse solutions with a large number of spurious coefficients. We propose two sparse VAR modelling methods that work well for high dimensional time series data, even when the number of time points is relatively low, by incorporating only statistically significant coefficients. In numerical experiments, our methods show consistently higher accuracy compared to other contemporary methods in recovering the true sparse model. The relative absence of spurious coefficients in our models permits more accurate, stable and efficient evaluation of derived quantities such as power spectrum, coherence and Granger causality. Using our models, sparse functional connectivity networks can be computed, in a reasonable time, from data comprising tens of thousands of channels/voxels. This far exceeds the capabilit ies of existing methods and enables simultaneous analysis of both local and global functional connectivity patterns and community structures in such large networks. When computed for fMRI data, these network and community structures are consistent over independent recording sessions and they show good spatial correspondence with known functional and anatomical regions of the brain. Our methods, when used to analyze ADHD fMRI data, provide new ways of differentiating between ADHD and typically developing children using global and node-level network measures.

11:00 to 11:30 -- Tea
11:30 to 12:15 Michael Small (University of Western Australia) Using networks to detect dynamical regime change in time series
12:15 to 13:30 -- Lunch
14:00 to 14:45 N. Nirmal Thyagu (VIT, Chennai, India) Persistent homology to characterize dynamics - a statistical analysis
14:45 to 15:30 Sarika Jalan (IITI, India) Optimized Evolution of Networks
15:30 to 16:00 -- Tea / Coffee break - Posters
16:15 to 17:00 R.I. Sujith (IITM, India) Complex Networks to Study Dynamical Transitions in Thermoacoustic Systems
17:00 to 17:45 Anurag Singh (NIT Delhi, India) Optimal Routing Strategies using Centrality measures in Time Varying Communication Networks
Friday, 29 June 2018
Time Speaker Title Resources
09:30 to 10:15 Niloy Ganguly (IIT Kharagpur, India) Opinion and Information Dynamics
10:15 to 11:00 M. Santhanam (IISERP, India) Transport on complex networks: Random walks, cover times and extreme events
11:00 to 11:30 -- Tea
11:30 to 12:15 Sitabhra Sinha/ Pranay Goel (IMSc, India & IISERP, India) Medicine and Public Health: A Complex Systems Approach?
12:15 to 14:00 -- Lunch
14:00 to 14:45 Samriddhi Sankar Ray (ICTS, India) Decimated Navier-Stokes turbulence
14:45 to 15:30 Prashant Manohar Gade (Nagpur University, India) Dynamic Phase Transitions on Networks
15:30 to 16:00 -- Tea
16:00 to 16:45 P. Muruganandam (Bharathidasan University, Trichy, India) Synchronization, multi-cluster oscillation death and chimera states in a network of oscillators: Role of initial conditions
16:45 to 17:30 Viktor Avrutin (University of Stuttgart, Germany) From power converters to low-dimensional piecewise smooth maps with an unpredictable number of switching manifolds: an unexpected journey
Saturday, 30 June 2018
Time Speaker Title Resources
10:15 to 11:00 Sitabhra Sinha (IMSc, India) Emergence of voluntary vaccination behavior in social networks of rational agents
11:00 to 11:30 -- Tea
11:30 to 12:15 Govindan Rangarajan (IISc, India) Sparse VAR and Network Representations of High Dimensional Time Series Data

Obtaining a sparse representation of high dimensional data is important since it provides an efficient representation of the data and facilitates its further analysis. Conventional Vector Autoregressive (VAR) modeling methods applied to such data result in non-sparse solutions with a large number of spurious coefficients. We propose two sparse VAR modelling methods that work well for high dimensional time series data, even when the number of time points is relatively low, by incorporating only statistically significant coefficients. In numerical experiments, our methods show consistently higher accuracy compared to other contemporary methods in recovering the true sparse model. The relative absence of spurious coefficients in our models permits more accurate, stable and efficient evaluation of derived quantities such as power spectrum, coherence and Granger causality. Using our models, sparse functional connectivity networks can be computed, in a reasonable time, from data comprising tens of thousands of channels/voxels. This far exceeds the capabilities of exis ting methods and enables simultaneous analysis of both local and global functional connectivity patterns and community structures in such large networks. When computed for fMRI data, these network and community structures are consistent over independent recording sessions and they show good spatial correspondence with known functional and anatomical regions of the brain. Our methods, when used to analyze ADHD fMRI data, provide new ways of differentiating between ADHD and typically developing children using global and node-level network measures.

12:15 to 14:00 -- Lunch
14:00 to 14:45 Amit Apte (ICTS, India) Mark ov random field model for the Indian monsoon rainfall

I will describe a representation of the Indian summer monsoon rainfall in terms of a probabilistic model based on a Markov Random Field, consisting of discrete state variables representing low and high rainfall at grid-scale and daily rainfall patterns across space and in time. These discrete states are conditioned on observed daily gridded rainfall data from the period 2000-2007. The model gives us a set of 10 spatial patterns of daily monsoon rainfall over India, which are robust over a range of user-chosen parameters as well as coherent in space and time. Each day in the monsoon season is assigned precisely one of the spatial patterns, that approximates the spatial distribution of rainfall on that day. Such approximations are quite accurate for nearly 95% of the days. Remarkably, these patterns are representative (with similar accuracy) of the monsoon seasons from 1901 to 2000 as well.

14:45 to 15:45 Samriddhi Sankar Ray (ICTS, India) Dynamics of non-spherical particles and chains
15:45 to 16:15 -- Tea
16:15 to 17:00 -- Round Table