Plan or not: Remote Human-robot Teaming with Incomplete Task Information. - Vignesh Narayanan; Yu Zhang 055; Nathaniel Mendoza; Subbarao Kambhampati (CoRR, 2014)

Automated Planning for Peer-to-peer Teaming and its Evaluation in Remote Human-Robot Interaction. - Vignesh Narayanan; Yu Zhang 055; Nathaniel Mendoza; Subbarao Kambhampati (HRI (Extended Abstracts), 2015)

A human factors analysis of proactive support in human-robot teaming. - Yu Zhang 055; Vignesh Narayanan; Tathagata Chakraborti; Subbarao Kambhampati (IROS, 2015)

Distributed Adaptive Optimal Regulation of Uncertain Large-Scale Linear Networked Control Systems Using Q-Learning. - Vignesh Narayanan; Sarangapani Jagannathan (SSCI, 2015)

Distributed event-sampled approximate optimal control of interconnected affine nonlinear continuous-time systems. - Vignesh Narayanan; Sarangapani Jagannathan (ACC, 2016)

Approximate optimal distributed control of uncertain nonlinear interconnected systems with event-sampled feedback. - Vignesh Narayanan; Sarangapani Jagannathan (CDC, 2016)

Event-sampled direct adaptive NN state-feedback control of uncertain strict-feedback system. - Nathan Szanto; Vignesh Narayanan; Sarangapani Jagannathan (CDC, 2016)

Event-sampled adaptive neural network control of robot manipulators. - Vignesh Narayanan; Sarangapani Jagannathan (IJCNN, 2016)

Distributed consensus-based event-triggered approximate control of nonholonomic mobile robot formations. - Haci Mehmet Guzey; Vignesh Narayanan; Sarangapani Jagannathan; Travis Dierks; Levent Acar (ACC, 2017)

Event-sampled control of quadrotor unmanned aerial vehicle using neural networks. - Nathan Szanto; Vignesh Narayanan; Sarangapani Jagannathan (ACC, 2017)

Online reinforcement with exploration for distributed control. - Vignesh Narayanan; Sarangapani Jagannathan (IJCNN, 2017)

Optimal sampling and regulation of uncertain interconnected linear continuous time systems. - Avimanyu Sahoo; Vignesh Narayanan; Sarangapani Jagannathan (SSCI, 2017)

Optimal event-triggered control of uncertain linear networked control systems: A co-design approach. - Avimanyu Sahoo; Vignesh Narayanan; Sarangapani Jagannathan (SSCI, 2017)

Optimal Event-triggered Control of Nonlinear Systems: A Min-max Approach. - Vignesh Narayanan; Avimanyu Sahoo; Sarangapani Jagannathan (ACC, 2018)

Approximate Optimal Distributed Control of Nonlinear Interconnected Systems Using Nonzero-Sum Games. - Vignesh Narayanan; Avimanyu Sahoo; Sarangapani Jagannathan (CDC, 2018)

Event-based Near Optimal Sampling and Tracking Control of Nonlinear Systems. - Avimanyu Sahoo; Vignesh Narayanan (CDC, 2018)

Adaptive Optimal Distributed Control of Linear Interconnected Systems. - Vignesh Narayanan; Avimanyu Sahoo; Sarangapani Jagannathan (SSCI, 2018)

Event-triggered Control of N-player Nonlinear Systems Using Nonzero-Sum Games. - Avimanyu Sahoo; Vignesh Narayanan; Sarangapani Jagannathan (SSCI, 2018)

Event-Triggered Distributed Control of Nonlinear Interconnected Systems Using Online Reinforcement Learning With Exploration. - Vignesh Narayanan; Sarangapani Jagannathan (IEEE Trans. Cybern., 2018)

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems. - Vignesh Narayanan; Sarangapani Jagannathan (IEEE Trans. Neural Networks Learn. Syst., 2018)

Event-Sampled Direct Adaptive NN Output- and State-Feedback Control of Uncertain Strict-Feedback System. - Nathan Szanto; Vignesh Narayanan; Sarangapani Jagannathan (IEEE Trans. Neural Networks Learn. Syst., 2018)

A Learning Framework for Controlling Spiking Neural Networks. - Vignesh Narayanan; Jason T. Ritt; Jr-Shin Li; ShiNung Ching (ACC, 2019)

Robust Population Transfer for Coupled Spin Ensembles. - Wei Zhang 092; Vignesh Narayanan; Jr-Shin Li (CDC, 2019)

Biophysically interpretable inference of single neuron dynamics. - Vignesh Narayanan; Jr-Shin Li; ShiNung Ching (J. Comput. Neurosci., 2019)

Optimization of sampling intervals for tracking control of nonlinear systems: A game theoretic approach. - Avimanyu Sahoo; Vignesh Narayanan (Neural Networks, 2019)

A Min-Max Approach to Event- and Self-Triggered Sampling and Regulation of Linear Systems. - Avimanyu Sahoo; Vignesh Narayanan; Sarangapani Jagannathan (IEEE Trans. Ind. Electron., 2019)

Event-Sampled Output Feedback Control of Robot Manipulators Using Neural Networks. - Vignesh Narayanan; Sarangapani Jagannathan; Kannan Ramkumar (IEEE Trans. Neural Networks Learn. Syst., 2019)

Approximate Optimal Distributed Control of Nonlinear Interconnected Systems Using Event-Triggered Nonzero-Sum Games. - Vignesh Narayanan; Avimanyu Sahoo; Sarangapani Jagannathan; Koshy George (IEEE Trans. Neural Networks Learn. Syst., 2019)

Learning to Control Neurons using Aggregated Measurements. - Yao-Chi Yu; Vignesh Narayanan; ShiNung Ching; Jr-Shin Li (ACC, 2020)

Finite-time Adaptive Optimal Output Feedback Control of Linear Systems with Intermittent Feedback. - Avimanyu Sahoo; Vignesh Narayanan; Qiming Zhao (SSCI, 2020)

Differential-game for resource aware approximate optimal control of large-scale nonlinear systems with multiple players. - Avimanyu Sahoo; Vignesh Narayanan (Neural Networks, 2020)

Adaptive Gain Observers for Distributed State Estimation of Linear Systems. - Avimanyu Sahoo; Vignesh Narayanan; Qiming Zhao (ACC, 2021)

Securing social media for seniors from information attacks: Modeling, detecting, intervening, and communicating risks. - Vignesh Narayanan; Brett W. Robertson; Andrea Hickerson; Biplav Srivastava; Bryant Walker Smith (TPS-ISA, 2021)

Learning to Control using Image Feedback. - Krishnan Raghavan; Vignesh Narayanan; Jagannathan Saraangapani (CoRR, 2021)

A Nested Two-Stage Clustering Method for Structured Temporal Sequence Data. - Liang Wang; Vignesh Narayanan; Yao-Chi Yu; Yikyung Park; Jr-Shin Li (Knowl. Inf. Syst., 2021)

Model Learning and Knowledge Sharing for Cooperative Multiagent Systems in Stochastic Environment. - Wei-Cheng Jiang; Vignesh Narayanan; Jr-Shin Li (IEEE Trans. Cybern., 2021)

Learning to Automate Follow-up Question Generation using Process Knowledge for Depression Triage on Reddit Posts. - Shrey Gupta; Anmol Agarwal; Manas Gaur; Kaushik Roy 009; Vignesh Narayanan; Ponnurangam Kumaraguru; Amit P. Sheth (CoRR, 2022)

KSAT: Knowledge-infused Self Attention Transformer - Integrating Multiple Domain-Specific Contexts. - Kaushik Roy 009; Yuxin Zi; Vignesh Narayanan; Manas Gaur; Amit P. Sheth (CoRR, 2022)

Event-Driven Off-Policy Reinforcement Learning for Control of Interconnected Systems. - Vignesh Narayanan; Hamidreza Modares; Sarangapani Jagannathan; Frank L. Lewis (IEEE Trans. Cybern., 2022)

Core Temperature Estimation of Lithium-ion Batteries Under Internal Thermal Faults Using Neural Networks. - Geetika Vennam; Avimanyu Sahoo; Vignesh Narayanan (CCTA, 2023)

Cook-Gen: Robust Generative Modeling of Cooking Actions from Recipes. - Revathy Venkataramanan; Kaushik Roy 009; Kanak Raj; Renjith Prasad; Yuxin Zi; Vignesh Narayanan; Amit P. Sheth (SMC, 2023)

Knowledge Graph Guided Semantic Evaluation of Language Models For User Trust. - Kaushik Roy 009; Tarun Garg; Vedant Palit; Yuxin Zi; Vignesh Narayanan; Amit P. Sheth (CoRR, 2023)

Process Knowledge-infused Learning for Clinician-friendly Explanations. - Kaushik Roy 009; Yuxin Zi; Manas Gaur; Jinendra Malekar; Qi Zhang 020; Vignesh Narayanan; Amit P. Sheth (CoRR, 2023)

Knowledge-Infused Self Attention Transformers. - Kaushik Roy 009; Yuxin Zi; Vignesh Narayanan; Manas Gaur; Amit P. Sheth (CoRR, 2023)

IERL: Interpretable Ensemble Representation Learning - Combining CrowdSourced Knowledge and Distributed Semantic Representations. - Yuxin Zi; Kaushik Roy 009; Vignesh Narayanan; Manas Gaur; Amit P. Sheth (CoRR, 2023)

A Planning Ontology to Represent and Exploit Planning Knowledge for Performance Efficiency. - Bharath Muppasani; Vishal Pallagani; Biplav Srivastava; Raghava Mutharaju; Michael N. Huhns; Vignesh Narayanan (CoRR, 2023)

Evaluating Chatbots to Promote Users' Trust - Practices and Open Problems. - Biplav Srivastava; Kausik Lakkaraju; Tarmo Koppel; Vignesh Narayanan; Ashish Kundu; Sachindra Joshi (CoRR, 2023)

Event-Triggered Optimal Adaptive Control of Partially Unknown Linear Continuous-Time Systems With State Delay. - Rohollah Moghadam; Vignesh Narayanan; Sarangapani Jagannathan (IEEE Trans. Syst. Man Cybern. Syst., 2023)

On safe and usable chatbots for promoting voter participation. - Bharath Muppasani; Vishal Pallagani; Kausik Lakkaraju; Shuge Lei; Biplav Srivastava; Brett W. Robertson; Andrea Hickerson; Vignesh Narayanan (AI Mag., 2023)

Interpretable Design of Reservoir Computing Networks Using Realization Theory. - Wei Miao; Vignesh Narayanan; Jr-Shin Li (IEEE Trans. Neural Networks Learn. Syst., 2023)

Expressive and Flexible Simulation of Information Spread Strategies in Social Networks Using Planning. - Bharath Muppasani; Vignesh Narayanan; Biplav Srivastava; Michael N. Huhns (AAAI, 2024)

Causal Event Graph-Guided Language-based Spatiotemporal Question Answering. - Kaushik Roy 009; Alessandro Oltramari; Yuxin Zi; Chathurangi Shyalika; Vignesh Narayanan; Amit P. Sheth (AAAI Spring Symposia, 2024)

Exploring Alternative Approaches to Language Modeling for Learning from Data and Knowledge. - Yuxin Zi; Kaushik Roy 009; Vignesh Narayanan; Amit P. Sheth (AAAI Spring Symposia, 2024)

Optimal Tracking of Uncertain Linear Discrete-Time Systems Using Trajectory-Dependent Lifelong Q-learning. - Maxwell Geiger; Vignesh Narayanan; Sarangapani Jagannathan (ACC, 2024)

Aperiodic Sensing and Data-Driven System Identification of Nonlinear Systems Using Chebyshev Pseudospectral Approach. - Arian Yousefian; Avimanyu Sahoo; Vignesh Narayanan (CDC, 2024)

Towards Effective Planning Strategies for Dynamic Opinion Networks. - Bharath Muppasani; Protik Nag; Vignesh Narayanan; Biplav Srivastava; Michael N. Huhns (NeurIPS, 2024)

Predicting Chaotic Systems with Quantum Echo-state Networks. - Erik Connerty; Ethan N. Evans; Gerasimos Angelatos; Vignesh Narayanan (CoRR, 2024)

RI2AP: Robust and Interpretable 2D Anomaly Prediction in Assembly Pipelines. - Chathurangi Shyalika; Kaushik Roy 009; Renjith Prasad; Fadi El Kalach; Yuxin Zi; Priya Mittal; Vignesh Narayanan; Ramy F. Harik; Amit P. Sheth (Sensors, 2024)

Cooperative Deep Q-Learning Framework for Environments Providing Image Feedback. - Krishnan Raghavan; Vignesh Narayanan; Sarangapani Jagannathan (IEEE Trans. Neural Networks Learn. Syst., 2024)

Moment-Based Reinforcement Learning for Ensemble Control. - Yao-Chi Yu; Vignesh Narayanan; Jr-Shin Li (IEEE Trans. Neural Networks Learn. Syst., 2024)

Duality of Ensemble Systems Through Moment Representations. - Vignesh Narayanan; Wei Zhang 092; Jr-Shin Li (IEEE Trans. Autom. Control., 2024)

A Novel Online System Identification Using Chebyshev Polynomial Basis of the Second Kind. - Arian Yousefian; Avimanyu Sahoo; Vignesh Narayanan (ACC, 2025)

Quantum Observers: A NISQ Hardware Demonstration of Chaotic State Prediction Using Quantum Echo-state Networks. - Erik Connerty; Ethan N. Evans; Gerasimos Angelatos; Vignesh Narayanan (CoRR, 2025)

A Novel Online Pseudospectral Method for Approximation of Nonlinear Systems Dynamics. - Arian Yousefian; Avimanyu Sahoo; Vignesh Narayanan (CoRR, 2025)

Iterative Reservoir Computing Networks for Reconstructing Irregular Time Series. - Yuan-Hung Kuan; Vignesh Narayanan; Jr-Shin Li (IEEE Trans. Neural Networks Learn. Syst., 2025)