Publications

Singh, A.K., Sridharan, K.S., Wu, S., Tirosh, O. and  Raghavan, M., (2025). In-silico neuro-musculoskeletal model demonstrates spasticity progression with descending motor tracts loss in simulated clinical triage. Computers in Biology and Medicine, 192, p.110270. 

Raghavan, M., (2025), Multidisciplinary IKS & Heritage: Areas of Study in an IKS-Inspired Academic System.” Saṃvādasaṃgrahaḥ Lecture Notes in IKS, pp 30–66., Ministry of Education, Government of India,  https://doi.org/10.71412/iks0007.ch2.  [Link]

Raghavan, M., Simha M S H, and Ramaswamy C R. (2025) Indic Knowledge Systems and Heritage: Elements & Design Principles. Saṃvādasaṃgrahaḥ: Lecture Notes in IKS,  pp 3–29., Ministry of Education, Government of India,  https://doi.org/10.71412/iks0007.ch1.

Krishna, S.H., Chinthapenta, V., Raghavan M., Unni., H.N., (2024)., Finite Element Modelling Of an Anatomically Accurate Human Spinal Cord. In Proceedings of the 10th World Congress on Electrical Engineering and Computer Systems and Sciences (EECSS'24)   DOI:10.11159/icbes24.110 

Mallampalli, K., Sarathy, K., Balasubramanian, R. and  Raghavan, M., (2024), July. Studying spinal feedback loops post tendon transfer surgery using the pincer grasp task: A Neuro-Musculoskeletal study using NEUROiD. In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1-4). IEEE. 

Ganguly, S., Chhaya, M.M., Jain, A., Koppula, A., Raghavan, M. and Sridharan, K.S., (2024). Mark3D–A semi-automated open-source toolbox for 3D head-surface reconstruction and electrode position registration using a smartphone camera video. Medical & Biological Engineering & Computing, pp.1-13. 

Singh, A.K., Sridharan, K.S., Wu, S., Tirosh, O. and Raghavan, M., (2024), June. Simulated Clinical Triage of Modified Tardieu Test for Lower Limb Spasticity. In 2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA) (pp. 1-6). IEEE. 

Medury, R.K., Kotak, B.P., Mandayam Rangayyan, Y., Sridharan, K.S., and Raghavan, M. “Indian Knowledge Systems & Heritage: State of the Industry Report,” (2024). Ministry of Education, Government of India. https://doi.org/10.71412/cinu1473. ISBN: 9788197811562

Rahaman, J., Jain, A., Sridharan, K.S. and Raghavan, M., (2023), October. A Rule-based Semi-automated OCR Postprocessing Method for Aligning Multi-language Transcripts with Multi-column Text. In 2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI) (pp. 1-9). IEEE. 

Raghavan, M., Simha, M.S.H. and C.R., Ramaswamy. (2023). Elements of Indic Knowledge Systems and Heritage. HTSR Institute, ISBN 978-81-964176-0-4.  [Link to book site] 

Mandayam Rangayyan, Y., Kidambi, S. and Raghavan, M., (2023). Deaths from undetected COVID-19 infections as a fraction of COVID-19 deaths can be used for early detection of an upcoming epidemic wave. Plos one, 18(3), p.e0283081. 

Iyengar, R.S., Mallampalli, K., Singh, A.K., Koppula, A., Sridharan, K.S. and Raghavan, M., (2023). The NEUROiD neuromusculoskeletal movement simulation platform. In Digital Human Modeling and Medicine (pp. 161-197). Academic Press. 

Kapardi, M., Pithapuram, M.V., Rangayyan, Y.M., Iyengar, R.S., Singh, A.K., Sripada, S. and  Raghavan, M., (2022). In-silico neuro musculoskeletal model reproduces the movement types obtained by spinal micro stimulation. Computer Methods and Programs in Biomedicine, p.106804. 

Pithapuram, M.V. and Raghavan, M., (2022). Automatic rule-based generation of spinal cord connectome model for a neuro-musculoskeletal limb in-silico. IOP SciNotes, 3(1), p.014001. 

Mahankali, N.S., Raghavan, M. and Channappayya, S.S.,( 2021). No-Reference Video Quality Assessment Using Voxel-wise fMRI Models of the Visual Cortex. IEEE Signal Processing Letters. 

Raghavan, M. ., and Maigur, R. K., (2021). Pratyāhāra – A Neuroscientific perspective of Yoga Shastra. Yoga Vijnana - The Science and Art of Yoga, 1(1). MDNIY. [pdf]

Raghavan, M. and Maigur, R.K., (2021). Indian Costumes through the Ages: Insights into Sartorial Choices Using Mathematical Biology. Archaeometry. https://doi.org/10.1111/arcm.12681 

Iyengar, R.S. and Raghavan, M., (2020), December.  MPI Parallelization of NEUROiD Models Using Docker Swarm. In 2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) (pp. 655-660). IEEE. 

Raghavan, M., Sridharan, K. S., & Mandayam Rangayyan, Y. (2020). Using epidemic simulators for monitoring an ongoing epidemic. Scientific reports, 10(1), 16571. https://doi.org/10.1038/s41598-020-73308-5 

Pithapuram, M. V., Iyengar, R S., Singh, A K., Raghavan, M. (2020)  A Neuromechanical model of lower limb with lumbosacral spinal cord controller for InSilico spinal cord stimulation experiments, in Virt. Phys. Hum. Conference (Accepted for Oral presentation) , 2020.

Prakash, S.C., Ganguly, S., Yadav, P.K., Raghavan, M. and Sridharan, K.S., (2020, July). Evaluation of a gamified upper-arm bimanual trainer for stroke patients-A healthy cohort study. In 2020 International Conference on Signal Processing and Communications (SPCOM) (pp. 1-5). IEEE.

 Mallampalli, K., Patel, S., Iyengar, R.S., Sridharan, K.S. and Raghavan, M., (2020, July). Tool for image annotation based on gaze. In 2020 International Conference on Signal Processing and Communications (SPCOM) (pp. 1-5). IEEE.

Singh, A. K., Pithapuram, M. V. and Raghavan, M. (2020) ‘Coupling neural simulations with inverse kinematics through proprioceptive afferents’, in Virt. Phys. Hum. Conference (Accepted as Poster) , 2020.

Iyengar, R. S., Pithapuram, M V., Singh, A K., Raghavan, M.  (2019) ‘Curated model development using NEUROiD: A web-based NEUROmotor integration and Design platform’, Frontiers in neuroinformatics. Frontiers, 13, p. 56.

Pithapuram, M. V., Iyengar, R. S. and Raghavan, M. (2019) ‘In silico Spinal cord model shows the viability of targeting segmental foci along rostrocaudal axis for eliciting a variety of movement types’, BMC Neuroscience, 28th Annual Computational Neuroscience Meeting: CNS*2019 in, 20(1), p. P254. doi: 10.1186/s12868-019-0538-0.

Sankaranarayani, R., Raghavan, M., Nalini, A., Laxmi, T.R. and Raju, T.R., (2014). ‘Reach task-associated excitatory overdrive of motor cortical neurons following infusion with ALS-CSF‘. Journal of Neural Transmission, 121(1), pp.49-58. 

Raghavan, M., Amrutur, B., Narayanan, R. and Sikdar, S.K., (2013). ‘Synconset waves and chains: spiking onsets in synchronous populations predict and are predicted by network structure‘. PloS one, 8(10), p.e74910. 

Ramamurthy, S. and Raghavan, M. (2013) ‘Filter design for synthesis of musical notes: A multidimensional feature-based approach’, in 2013 IEEE International Conference on Signal and Image Processing Applications. IEEE, pp. 106–111.

Raghavan, M., Amrutur, B., Srinivas, K.V. and Sikdar, S.K.  (2012) ‘A study of epileptogenic network structures in rat hippocampal cultures using first spike latencies during synchronization events’, Physical biology. IOP Publishing, 9(5), p. 56002.

Preprints and papers under review

Iyengar, R. S., Mallampalli, K., Raghavan, M., (2021) ‘A novel paradigm for  deep reinforcement learning of biomimetic systems‘, bioRxiv.