We study the structure, dynamics and resilience of complex networks — from brain and climate systems to social, technological and higher-order networks.
Edge Cases 2026 highlights surprising network science research, and applications of network science in unconventional domains. Dr Divya presented insights on "Winning at Chess Without Search: Predicting Game Outcomes from Evolving Interaction Networks"
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Machine Learning: From Fundamentals to Deployment - Dr Jisha delivered sessions covering key concepts and practical aspects of Machine Learning.
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Network Neuroscience Presented our work on EEG recurrence networks and Major Depressive Disorder at the Network Neuroscience Satellite of NetSci 2026. Grateful for the opportunity to share our findings and connect with researchers in network neuroscience and complex systems.
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Collaboration with 𝘊𝘖𝘕𝘕𝘱𝘭𝘦𝘹𝘪𝘵𝘺 𝘓𝘢𝘣 Ms. Julie presented her work as one of the Data Blitz presenters. She also had the opportunity to present the poster and engage in insightful discussions with researchers and clinicians working at the forefront of ultra-high-field MRI and brain imaging research.
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An invited lecture on “Complex Network Approach for Recurrence Analysis of Time Series” was delivered during the ADMA-ICDM 2025 pre-conference workshop on Network Analysis.
Explore events →The group participated in the Network Science Society's winter flagship conference in India, with a focus session and student poster presentations.
View highlights →Funding supported research on fingerprinting and communicability of functional brain networks using graph-theoretic methods.
See projects →A five-day workshop on Network Data Analysis was organised jointly with the Data Science Research Group at IIIT Kottayam.
Read more →Our research combines mathematical foundations with computational network analysis to uncover patterns, vulnerabilities, communities and emergent behaviour in complex systems.
Robustness, vulnerability, sparsification and structural analysis.
Interactions across layers, coupling and resilience of interconnected systems.
Brain connectivity, recurrence networks and biomarkers from neural signals.
Hypergraphs, higher-order interactions and structures beyond pairwise links.
Graph representation learning, community structures and data-driven network models.
Analysing complex relational data using scalable computational methods.
We investigate how real-world networks respond to failures, attacks and structural changes, and how network models can reveal vulnerabilities and guide resilient system design.
Explore our research, people and current projects.
