My multidisciplinary research interest lies in natural and engineered complex systems, whose functions emerge from the interactions of its multiple sub-components. I have used reduced-order (parsimonious) models to analyze or to control the functions of such systems in mechanical and biomedical engineering applications. Through my mechanical engineering PhD research, I have developed novel physics-informed reduced-order models of response to external perturbations, for a wide-range of complex mechanical systems [J(2-5), C(2-3), A(1-2)]. Furthermore, I computationally demonstrated the utility of such models for uncertainty quantification and system identification [J2]. Through my ongoing translational neuroengineering Postdoctoral research, I have contributed novel algorithms to infer data-informed, reduced-order models of electrophysiological activity in the brain [C(4,5,7,8)]. Furthermore, I have developed a novel closed-loop anesthesia delivery (CLAD) system by leveraging one such statistical model of neural response due to anesthetic dosing. I have experimentally demonstrated that this CLAD system can maintain precise brain states in an unconscious non-human primate (NHP) for a prolonged period of time [A3].
[J7] B.L. Edlow, M.E. Barra, D.W. Zhou, A.S. Foulkes, S.B. Snider, Z.D. Threlkeld, S. Chakravarty, J.E. Kirsch, S.T. Chan, S.L. Meisler, T.P. Bleck, J.J. Fins, J.T. Giacino, L.R. Hochberg, K. Solt, E.N. Brown, Y.G. Bodien. Personalized connectome mapping to guide targeted therapy and promote recovery of consciousness in the intensive care unit. Neurocritical Care. 2020. (in press; medArxiv)
[J6] S. Koch, I. Feinkohl, S. Chakravarty, V. Windmann, G. Lichtner, T. Pischon, E. N. Brown, C. Spies, Cognitive impairment is associated with absolute intraoperative frontal alpha-band power but not with baseline alpha-band power - a pilot study. Dementia and Geriatric Cognitive Disorders, 2019.
[J5] S. Chakravarty, S. Sen, Possibility of useful mechanical energy from noise - the solitary wave train problem in the granular chain revisited. Granular Matter, 2018.
[J4] S. Chakravarty, S. Das, A. R. Hadjesfandiari, G. F. Dargush, Variational inequalities for heterogeneous microstructures based on couple stress theory. International Journal for Multiscale Computational Engineering, 2018.
[J3] S. Chakravarty, A. R. Hadjesfandiari, G. F. Dargush, A penalty-based finite element framework for couple stress elasticity, Finite Elements in Analysis and Design, 2017.
[J2] S. Das, S. Chakravarty, Predictive algorithm for detection of micro-cracks from macro-scale observables, SIAM Journal of Uncertainty Quantification, 2016.
[J1] B. Mahanty, R. K. Agrawal, S. Shrin, S. Chakravarty, Hybrid approach to optimal packing using genetic algorithm and coulomb potential algorithm, Materials and Manufacturing Processes, 2007.
[C11] G. Schamberg*, S. Chakravarty*, T. E. Baum, E. N. Brown, Inferring neural dynamics during burst suppression using a neurophysiology-inspired switching state-space model. IEEE ACSSC, 2020. (Invited, *co-first authors) (arXiv)
[C10] S. Chakravarty*, A. S. Waite*, J. Abel, E. N. Brown, A simulation-based comparative analysis of PID and LQG control for closed-loop anesthesia delivery. IFAC World Congress, 2020. (Accepted, *co-first authors) (arxiv)
[C9] J. Abel, M. Badgeley, T. E. Baum, S. Chakravarty, P. Purdon, E. N. Brown, Constructing a control-ready model of EEG signal during general anesthesia in humans. IFAC World Congress, 2020. (Accepted)
[C8] S. Chakravarty, Z. D. Threlkeld, Y. G. Bodien, B. L. Edlow, E. N. Brown, A state-space model for dynamic functional connectivity. IEEE ACSSC, 2019. (Invited) (arxiv)
[C7] S. Chakravarty*, T. E. Baum*, J. An, P. Kahali, E. N. Brown, A hidden semi-Markov model for estimating burst suppression EEG. IEEE EMBC, 2019. (*co-first authors)
[C6] S. Subramanian, S. Chamadia, S. Chakravarty, Arousal Detection in Obstructive Sleep Apnea using Physiology-Driven Features. IEEE Computing in Cardiology, 2018.
[C5] A. H. Song*, S. Chakravarty*, E. N. Brown, A Smoother State Space Multitaper Spectrogram. IEEE EMBC, 2018. (*co-first authors)
[C4] S. Chakravarty, K. Nikolaeva, D. Kishnan, F. J. Flores, P. L. Purdon, E. N. Brown, Pharmacodynamic modeling of propofol-induced general anesthesia in young adults. IEEE NIH HIPOCT, 2017.
[C3] S. Das, S. Chakravarty, Reliable prediction of micro-anomalies from macro-observables, SPIE Health Monitoring of Structural and Biological Systems, 2014.
[C2] S. Das, S. Chakravarty, Characterization of Micro-anomalies from Macro-scale Response, AIAA/ ASME/ ASCE/ AHS/ ASC Structures, Structural Dynamics, and Material Conference, 2013.
[C1] M.S. Narayanan, S. Chakravarty, H. Shah, V.N. Krovi, Kinematic, Static and workspace analysis of a 6-PUS parallel manipulator, ASME IDETC/CIE Conference, 2010.
[A3] S. Chakravarty*, J. Donoghue*, A.S. Waite, M. Mahnke, I.C. Rice, E.K. Miller, E.N. Brown. Closed-loop anesthesia delivery in non-human primates. (*co-first authors)
2nd Place in poster competition organized by Quantitative Systems Pharmacology (QSP) Summit 2020
Dr. Brown discusses representative results in https://www.youtube.com/watch?v=eKmOIPpcI3g between 33:43 min - 35:25 min
One of only 135 abstracts accepted for dynamic poster presentation in Society for Neuroscience Annual Meeting, 2019; Picower coverage
[A2] S. Chakravarty. New Bounds on Tangential Constitutive Elasticity Matrix for Non-Linear Elastic Materials, a Multi-Scale Approach. PhD dissertation research advised by Sonjoy Das.
[A1] S. Chakravarty. Detection of Micro-Anomalies from Macroscale Response. PhD dissertation research advised by Sonjoy Das.
1st Place (shared with 2 co-competitors) in Engineering Mechanics Institute 2013 Probabilistic Methods Paper Competition