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Controllability of Functional Brain Networks

--Prof. Ramkrishna Pasumarthy-- The brain has undeniably been the most enigmatic organ of the human body. To further our understanding of this mysterious organ, a talk titled “Controllability of Functional Brain Networks” was organized on 2nd September 2021 as a part of the third AI impact seminar. The talk was delivered by Professor Ramkrishna Pasumarthy who is an Associate Professor at IIT Madras. Prof. Pasumarthy started the talk by saying that for a long time most brain modelling was questionnaire-based and only now the availability of huge amounts of FMRI data is driving advances in this field.

• Apr 11, 2022

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projects

Nirav Bhatt , Shankar Narasimhan

Learning Mesh and Multiple Conserved Networks From Data

network science network construction

publications

Verification and Rectification of Error in Topology of Conserved Networks

Satya Jayadev P, Arsh Bawa, Nirav Bhatt,

IFAC-PapersOnLine

https://doi.org/10.1016/j.ifacol.2022.11.026

Benchmarking and Analysing Unsupervised Network Representation Learning and the Illusion of Progress

Saket Gurukar, Priyesh Vijayan, srinivasan parthasarathy, Balaraman Ravindran, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel,

Transactions on Machine Learning Research.

https://openreview.net/forum?id=GvF9ktXI1V

Effect of dormant spare capacity on the attack tolerance of complex networks

Sai Saranga Das M, Karthik Raman,

Physica A: Statistical Mechanics and its Applications

https://doi.org/10.1016/j.physa.2022.127419

Discovering adaptation-capable biological network structures using control-theoretic approaches

Priyan Bhattacharya, Karthik Raman, Arun K. Tangirala,

PLOS Computational Biology

https://doi.org/10.1371/journal.pcbi.1009769

On Strong Structural Controllability of Temporal Networks

Manikya Valli Srighakollapu, Rachel Kalpana Kalaimani, Ramkrishna Pasumarthy,

IEEE Control Systems Letters

https://doi.org/10.1109/LCSYS.2021.3133320

Predicting unknown directed links of conserved networks from flow data

Satya Jayadev Pappu, Ramkrishna Pasumarthy, Nirav Bhatt,

Journal of Complex Networks

https://doi.org/10.1093/comnet/cnab037

Metric Learning for comparison of HMMs using Graph Neural Networks

Rajan Kumar Soni, K Seshadri, B Ravindran,

To appear in the Proceedings of the Thirteenth Asian Conference on Machine Learning (ACML 2021)

https://proceedings.mlr.press/v157/soni21a/soni21a.pdf

Event-Triggered Control Design for Systems With Exogenous Inputs: Application for Auto-Scaling of Cloud-Hosted Web Servers

Durgesh Singh, Kshama Dwarakanath, Ramkrishna Pasumarthy,

IEEE Transactions on Systems, Man, and Cybernetics: Systems

https://doi.org/10.1109/TSMC.2021.3121681

A Joint Training Framework for Open-World Knowledge Graph Embeddings

Karthik Venkat Ramanan, Beethika Tripathi, Mitesh M. Khapra, B Ravindran,

To appear in the proceedings of the Automated Knowledge Base Construction Conference (AKBC 2021)

https://www.akbc.ws/2021/assets/pdfs/HozL9BGbnKr.pdf

Optimizing Driver Nodes for Structural Controllability of Temporal Networks

Manikya Valli Srighakollapu, Rachel Kalpana Kalaimani, Ramkrishna Pasumarthy,

IEEE Transactions on Control of Network Systems

https://doi.org/10.1109/TCNS.2021.3106454

A priori parameter identifiability in models with non-rational functions

Rishabh Jain, Sridharakumar Narasimhan, Nirav P. Bhatt,

Automatica

https://doi.org/10.1016/j.automatica.2019.108513