[17] 

Andrew Branen, Yuyu Yao, Mayuresh Kothare, Babak Mahmoudi and Gautam Kumar. Sparc: closed-loop optimization of vagus nerve stimulation for the cardiovascular system using long short-term memory neural network. Submitted In Society for Neuroscience Annual Meeting, July 15, 2021. 

[16] 

Joseph Schmalz and Gautam Kumar. A computational model of the dopaminergic modulation of hippocampal Schaffer collateral-CA1 long-term plasticity. In 30th Annual Computational Neurocience (CNS) Meeting, July 04, 2021 (Contributed Oral Presentation). 

[15] 

Andrew Branen, Babak Mahmoudi, Mayuresh Kothare and Gautam Kumar. Model Predictive Control of Vagus Nerve Stimulation in the Rat Cardiac System Using Long Short-Term Memory Network. In AICHE Annual Meeting, 2021. 

[14] 

Andrew Branen, Yuyu Yao, Mayuresh Kothare, Babak Mahmoudi and Gautam Kumar. Mapping Vagus Nerve Stimulation Parameters to Cardiac Physiology using Long Short-term Memory Network. Accepted in IEEE EMBC, 2021. 

[13] 

Joseph Schmalz and Gautam Kumar. A computational model of dopaminergic modulation of hippocampal Schaffer collateral-CA1 long-term plasticity. Accepted in Journal of Computational Neuroscience, May 2021. [  DOI | http ] 

[12] 

Joseph Schmalz, Gautam Kumar and Mayuresh Kothare. Controlling Epileptic Seizures using Forced Temporal Spike-Time Stimulation. In Society for Neuroscience Annual Meeting, 2020. 

[11] 

Benjamin Plaster, Niko Hansen and Gautam Kumar. Discovering Latent Dynamics Embedded in Large-Scale Neural Spiking Activity. In AICHE Annual Meeting, 2020. 

[10] 

Joseph Schmalz and Gautam Kumar. Spatiotemporal Dopaminergic Modulation of Schaffer Collateral-CA1 Plasticity: A Computational Modeling Approach. In AICHE Annual Meeting, 2020. 

[9] 

Andrew Branen and Gautam Kumar. Computational Modeling to Understand the Spatiotemporal Cholinergic Modulation of Hippocampal Synaptic Plasticity. In AICHE Annual Meeting, 2020. 

[8] 

Benjamin Plaster and Gautam Kumar. Data-driven predictive modeling of neuronal dynamics using long short-term memory. Algorithms, 12(10), 203, September 2019. [  (Simulation Codes) | http ] 

[7] 

Benjamin Plaster and Gautam Kumar. Hybrid deep neural network based predictive modeling of dynamical systems. Submitted, 2019. (Manuscript-Authours' Version) 

[6] 

Joseph Schmalz and Gautam Kumar. Controlling synchronization of spiking neuronal networks by harnessing synaptic plasticity. Frontiers In Computational Neuroscience, 13(61):1--17, September 2019. [ bib | (Simulation Codes) | DOI | http ] 

[5] 

Joseph Schmalz and Gautam Kumar. Spatiotemporal dopaminergic modulation of Schaffer collateral - CA1 plasticity: A computational modeling approach. In Society for Neuroscience Annual Meeting, 2019. 

[4] 

Joseph Schmalz and Gautam Kumar. Disruption of homeostasis of the Basal Ganglia circuit in Parkinson's disease. In Society for Neuroscience Annual Meeting, November 2018. 

[3] 

Joseph Schmalz and Gautam Kumar. Designing stochastic model predictive control based neural interface to restore communication between brain regions. In AICHE Annual Meeting, October-November 2018. (Abstract) 

[2] 

Joseph Schmalz and Gautam Kumar. Understanding the Basal Ganglia dynamic transition from the healthy to the Parkinsonian state. In AICHE Annual Meeting, October-November 2018. (Abstract) 

[1] 

Joseph Schmalz and Gautam Kumar. Controlling synchronization in spiking neuronal networks by harnessesing plasticity. In Minnesota Neuromodulation Symposium, Minneapolis, MN, April 2018. 

[29] 

Gautam Kumar, Delsin Menolascino, and ShiNung Ching. Sensitivity of linear systems to input orientation and novelty. Automatica, 93:462--468, 2018. 

[28] 

Sensen Lu, Gautam Kumar, and ShiNung Ching. Regularization-free synthesis of stable, informationoptimal plasticity rules in recurrent networks. In Computational and Systems Neuroscience (COSYNE) Meeting, Salt Lake City, Utah, March 2016. 

[27] 

Gautam Kumar and ShiNung Ching. The geometry of plasticity-induced sensitization in isoinhibitory rate motifs. Neural Computation, 2016. 

[26] 

Gautam Kumar, Mayuresh V Kothare, Nitish V Thakor, Marc H Schieber, Hongguang Pan, Baocang Ding, and Weimin Zhong. Designing closed-loop brain-machine interfaces using model predictive control. Technologies, 4(2):18, 2016. 

[25] 

Gautam Kumar, Seul Ah Kim, and ShiNung Ching. A control-theoretic approach to neural pharmacology: Optimizing drug selection and dosing. Journal of Dynamic Systems, Measurement, and Control, 138(8):084501, 2016. 

[24] 

Gautam Kumar and ShiNung Ching. Plasticity-induced sensitization in recurrent e-i networks. In Society for Neuroscience Annual Meeting, Chicago, IL, October 2015. 

[23] 

Hongguang Pan, Baocang Ding, Weimin Zhong, Gautam Kumar, and Mayuresh V Kothare. Designing closed-loop brain-machine interfaces with network of spiking neurons using mpc strategy. In American Control Conference (ACC), 2015, pages 2543--2548. IEEE, 2015. 

[22] 

Gautam Kumar, Delsin Menolascino, MohammadMehdi Kafashan, and ShiNung Ching. Controlling linear networks with minimally novel inputs. In American Control Conference (ACC), 2015, pages 5896--5900. IEEE, 2015. 

[21] 

Gautam Kumar and ShiNung Ching. Design of optimally sparse dosing strategies for neural pharmacology. In American Control Conference (ACC), 2015, pages 5865--5870. IEEE, 2015. 

[20] 

ShiNung Ching and Gautam Kumar. Measuring the expressiveness of plastic neuronal networks. In IEEE EMBS BRAIN Grand Challenges Conference, Washington, DC, November 2014. 

[19] 

Gautam Kumar and ShiNung Ching. Maximizing relaxation time in oscillator networks with implications for neurostimulation. In Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, pages 6589--6592. IEEE, 2014. 

[18] 

Gautam Kumar and Mayuresh V Kothare. Trapping brownian ensemble optimally using broadcast stochastic receding horizon control. Automatica, 50(2):389--398, 2014. 

[17] 

Gautam Kumar, Marc H Schieber, Nitish V Thakor, and Mayuresh V Kothare. Designing closed-loop brain-machine interfaces using charge balanced biphasic stimulating currents. In Society for Neuroscience Annual Meeting, San Diego, CA, November 2013. 

[16] 

Gautam Kumar, Marc H Schieber, Nitish V Thakor, and Mayuresh V Kothare. Designing closed-loop brain-machine interfaces using optimal receding horizon control. In American Control Conference (ACC), 2013, pages 5029--5034. IEEE, 2013. 

[15] 

Gautam Kumar and Mayuresh V Kothare. Broadcast stochastic receding horizon control of multi-agent systems. Automatica, 49(12):3600--3606, 2013. 

[14] 

Gautam Kumar and Mayuresh V Kothare. On the continuous differentiability of inter-spike intervals of synaptically connected cortical spiking neurons in a neuronal network. Neural computation, 25(12):3183--3206, 2013. 

[13] 

Gautam Kumar, William E Schiesser, and Mayuresh V Kothare. A quantitative assessment of the izhikevich neuron model against experimental data. In AICHE Annual Meeting, Pittsburgh, PA, November 2012. 

[12] 

Gautam Kumar and Mayuresh V Kothare. Regulating and trapping an ensemble of brownian particles by broadcast the stochastic receding horizon control policy. In AICHE Annual Meeting, Pittsburgh, PA, October 2012. 

[11] 

Gautam Kumar, Nitish V Thakor, and Mayuresh V Kothare. Cortical neuronal network based neuroprosthetic finger control: A control theoretic approach. In Society for Neuroscience Annual Meeting, Washington, DC, November 2011. 

[10] 

Gautam Kumar, Nitish V Thakor, and Mayuresh V Kothare. Control of a motor intended neural prosthetic finger using a network of cortical motor neurons. In AICHE Annual Meeting, Minneapolis, MN, October 2011. 

[9] 

Gautam Kumar, Vikram Aggarwal, Nitish V Thakor, Marc H Schieber, and Mayuresh V Kothare. An optimal control problem in closed-loop neuroprostheses. In Decision and Control and European Control Conference (CDC-ECC), 2011 50th IEEE Conference on, pages 53--58. IEEE, 2011. 

[8] 

Gautam Kumar, Vikram Aggarwal, Nitish V Thakor, Marc H Schieber, and Mayuresh V Kothare. A control approach towards closed-loop neural prosthesis. In Society for Neuroscience Annual Meeting, San Diego, CA, November 2010. 

[7] 

Gautam Kumar, Vikram Aggarwal, Nitish V Thakor, Marc H Schieber, and Mayuresh V Kothare. Optimal parameter estimation of stochastic izhikevich single neuron model using experimental inter-spike interval data. In AICHE Annual Meeting, Salt Lake City, Utah, November 2010. 

[6] 

Gautam Kumar, Vikram Aggarwal, Nitish V Thakor, Marc H Schieber, and Mayuresh V Kothare. Design and control of a closed-loop neural prosthesis. In AICHE Annual Meeting, Salt Lake City, Utah, November 2010. 

[5] 

Gautam Kumar and Mayuresh V Kothare. A mathematical theory of manipulating suspended multiple brownian particles simultaneously in a solution. In AICHE Annual Meeting, Salt Lake City, Utah, November 2010. 

[4] 

Gautam Kumar, Vikram Aggarwal, Nitish V Thakor, Marc H Schieber, and Mayuresh V Kothare. Optimal parameter estimation of the izhikevich single neuron model using experimental inter-spike interval (isi) data. In American Control Conference (ACC), 2010, pages 3586--3591. IEEE, 2010. 

[3] 

Gautam Kumar and Mayuresh V Kothare. Broadcast model predictive control of multi-cellular system. In AICHE Anuual Meeting, Nashville, TN, November 2009. 

[2] 

Gautam Kumar, Vikram Aggarwal, Nitish V Thakor, and Mayuresh V Kothare. Optimal control of closed-loop neural prostheses. In AICHE Annual Meeting, Nashville, TN, November 2009. 

[1] 

Gautam Kumar, Pradeep Y Tiwari, Vincent Marcopoli, and Mayuresh V Kothare. A study of a gun-turret assembly in an armored tank using model predictive control. In American Control Conference, 2009. ACC'09., pages 4848--4853. IEEE, 2009.