Development of a Fuzzy Sliding Mode Controller with adaptive tuning technique for a MRI guided robot in the human vasculature. - Aritra Mitra; Laxmidhar Behera (INDIN, 2015)

An approach for distributed state estimation of LTI systems. - Aritra Mitra; Shreyas Sundaram (Allerton, 2016)

Secure distributed observers for a class of linear time invariant systems in the presence of Byzantine adversaries. - Aritra Mitra; Shreyas Sundaram (CDC, 2016)

Distributed functional observers for LTI systems. - Aritra Mitra; Shreyas Sundaram (CDC, 2017)

Secure Distributed State Estimation of an LTI System Over Time-Varying Networks and Analog Erasure Channels. - Aritra Mitra; Shreyas Sundaram (ACC, 2018)

On the Impact of Trusted Nodes in Resilient Distributed State Estimation of LTI Systems. - Aritra Mitra; Waseem Abbas; Shreyas Sundaram (CDC, 2018)

A Novel Switched Linear Observer for Estimating the State of a Dynamical Process with a Mobile Agent. - Aritra Mitra; Shreyas Sundaram (CDC, 2018)

Resilient Distributed State Estimation for LTI Systems. - Aritra Mitra; Shreyas Sundaram (CoRR, 2018)

Distributed Observers for LTI Systems. - Aritra Mitra; Shreyas Sundaram (IEEE Trans. Autom. Control., 2018)

Finite-Time Distributed State Estimation over Time-Varying Graphs: Exploiting the Age-of-Information. - Aritra Mitra; John A. Richards; Saurabh Bagchi; Shreyas Sundaram (ACC, 2019)

A New Approach for Distributed Hypothesis Testing with Extensions to Byzantine-Resilience. - Aritra Mitra; John A. Richards; Shreyas Sundaram (ACC, 2019)

When is the Secure State-Reconstruction Problem Hard? - Yanwen Mao; Aritra Mitra; Shreyas Sundaram; Paulo Tabuada (CDC, 2019)

A Communication-Efficient Algorithm for Exponentially Fast Non-Bayesian Learning in Networks. - Aritra Mitra; John A. Richards; Shreyas Sundaram (CDC, 2019)

Resilient distributed state estimation with mobile agents: overcoming Byzantine adversaries, communication losses, and intermittent measurements. - Aritra Mitra; John A. Richards; Saurabh Bagchi; Shreyas Sundaram (Auton. Robots, 2019)

Byzantine-resilient distributed observers for LTI systems. - Aritra Mitra; Shreyas Sundaram (Autom., 2019)

Event-Triggered Distributed Inference. - Aritra Mitra; Saurabh Bagchi; Shreyas Sundaram (CDC, 2020)

Distributed Hypothesis Testing and Social Learning in Finite Time with a Finite Amount of Communication. - Shreyas Sundaram; Aritra Mitra (CoRR, 2020)

Online Federated Learning. - Aritra Mitra; Hamed Hassani; George J. Pappas (CDC, 2021)

Federated Learning with Incrementally Aggregated Gradients. - Aritra Mitra; Rayana H. Jaafar; George J. Pappas; Hamed Hassani (CDC, 2021)

TimeFabric: Trusted Time for Permissioned Blockchains. - Aritra Mitra; Christian Gorenflo; Lukasz Golab; Srinivasan Keshav (FAB, 2021)

Near-Optimal Data Source Selection for Bayesian Learning. - Lintao Ye; Aritra Mitra; Shreyas Sundaram (L4DC, 2021)

Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients. - Aritra Mitra; Rayana H. Jaafar; George J. Pappas; Hamed Hassani (NeurIPS, 2021)

Achieving Linear Convergence in Federated Learning under Objective and Systems Heterogeneity. - Aritra Mitra; Rayana H. Jaafar; George J. Pappas; Hamed Hassani (CoRR, 2021)

Exploiting Heterogeneity in Robust Federated Best-Arm Identification. - Aritra Mitra; Hamed Hassani; George J. Pappas (CoRR, 2021)

A New Approach to Distributed Hypothesis Testing and Non-Bayesian Learning: Improved Learning Rate and Byzantine Resilience. - Aritra Mitra; John A. Richards; Shreyas Sundaram (IEEE Trans. Autom. Control., 2021)

On the Impacts of Redundancy, Diversity, and Trust in Resilient Distributed State Estimation. - Aritra Mitra; Faiq Ghawash; Shreyas Sundaram; Waseem Abbas (IEEE Trans. Control. Netw. Syst., 2021)

Distributed Inference With Sparse and Quantized Communication. - Aritra Mitra; John A. Richards; Saurabh Bagchi; Shreyas Sundaram (IEEE Trans. Signal Process., 2021)

Distributed Statistical Min-Max Learning in the Presence of Byzantine Agents. - Arman Adibi; Aritra Mitra; George J. Pappas; Hamed Hassani (CDC, 2022)

Peer-to-Peer Non-Bayesian Learning in Finite Time with a Finite Amount of Communication. - Shreyas Sundaram; Aritra Mitra (CDC, 2022)

Evaluating Usefulness of C Comments using SVM and Naïve Bayes Classifier. - Aritra Mitra (FIRE (Working Notes), 2022)

Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds. - Aritra Mitra; Arman Adibi; George J. Pappas; Hamed Hassani (NeurIPS, 2022)

On the computational complexity of the secure state-reconstruction problem. - Yanwen Mao; Aritra Mitra; Shreyas Sundaram; Paulo Tabuada (Autom., 2022)

A Survey of Graph-Theoretic Approaches for Analyzing the Resilience of Networked Control Systems. - Mohammad Pirani; Aritra Mitra; Shreyas Sundaram (CoRR, 2022)

Distributed State Estimation Over Time-Varying Graphs: Exploiting the Age-of-Information. - Aritra Mitra; John A. Richards; Saurabh Bagchi; Shreyas Sundaram (IEEE Trans. Autom. Control., 2022)

Assessing the Utility of C Comments with SVM and Naïve Bayes Classifier. - Aritra Mitra (FIRE (Working Notes), 2023)

Linear Stochastic Bandits over a Bit-Constrained Channel. - Aritra Mitra; Hamed Hassani; George J. Pappas (L4DC, 2023)

Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity. - Han Wang 016; Aritra Mitra; Hamed Hassani; George J. Pappas; James Anderson 001 (CoRR, 2023)

Federated TD Learning Over Finite-Rate Erasure Channels: Linear Speedup Under Markovian Sampling. - Nicolò Dal Fabbro; Aritra Mitra; George J. Pappas (IEEE Control. Syst. Lett., 2023)

Graph-theoretic approaches for analyzing the resilience of distributed control systems: A tutorial and survey. - Mohammad Pirani; Aritra Mitra; Shreyas Sundaram (Autom., 2023)

Towards Robust Multi-Agent Reinforcement Learning. - Aritra Mitra (AAAI Spring Symposia, 2024)

Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling. - Arman Adibi; Nicolò Dal Fabbro; Luca Schenato 001; Sanjeev R. Kulkarni; H. Vincent Poor; George J. Pappas; Hamed Hassani; Aritra Mitra (AISTATS, 2024)

Min-Max Optimization Under Delays. - Arman Adibi; Aritra Mitra; Hamed Hassani (ACC, 2024)

Finite- Time Analysis of Asynchronous Multi-Agent TD Learning. - Nicolò Dal Fabbro; Arman Adibi; Aritra Mitra; George J. Pappas (ACC, 2024)

DASA: Delay-Adaptive Multi-Agent Stochastic Approximation. - Nicolò Dal Fabbro; Arman Adibi; H. Vincent Poor; Sanjeev R. Kulkarni; Aritra Mitra; George J. Pappas (CDC, 2024)

Robust Q-Learning under Corrupted Rewards. - Sreejeet Maity; Aritra Mitra (CDC, 2024)

On the Convergence of Policy Gradient for Designing a Linear Quadratic Regulator by Leveraging a Proxy System. - Lintao Ye; Aritra Mitra; Vijay Gupta (CDC, 2024)

Towards Fast Rates for Federated and Multi-Task Reinforcement Learning. - Feng Zhu 025; Robert W. Heath Jr.; Aritra Mitra (CDC, 2024)

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning. - Chenyu Zhang 002; Han Wang 016; Aritra Mitra; James Anderson 001 (ICLR, 2024)

Towards model-free LQR control over rate-limited channels. - Aritra Mitra; Lintao Ye; Vijay Gupta 001 (L4DC, 2024)

Federated TD Learning with Linear Function Approximation under Environmental Heterogeneity. - Han Wang 016; Aritra Mitra; Hamed Hassani; George J. Pappas; James Anderson 001 (Trans. Mach. Learn. Res., 2024)

Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning. - Aritra Mitra; George J. Pappas; Hamed Hassani (Trans. Mach. Learn. Res., 2024)

A Human-Augmenting Resource/Performance Co-Design Tool for Real-Time Distributed Control Systems. - Haoguang Yang; Aritra Mitra; Yanzhe Cui; Shreyas Sundaram; Xin Ma; Steve Sullivan; Richard M. Voyles (IEEE Trans. Syst. Man Cybern. Syst., 2024)

Adversarially-Robust TD Learning with Markovian Data: Finite-Time Rates and Fundamental Limits. - Sreejeet Maity; Aritra Mitra (AISTATS, 2025)

Outlier-Robust Linear System Identification Under Heavy-Tailed Noise. - Vinay Kanakeri; Aritra Mitra (L4DC, 2025)

A Simple Finite-Time Analysis of TD Learning With Linear Function Approximation. - Aritra Mitra (IEEE Trans. Autom. Control., 2025)

Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation under Markovian Sampling. - Feng Zhu 025; Aritra Mitra; Robert W. Heath Jr. (CoRR, 2025)

Boosting-Enabled Robust System Identification of Partially Observed LTI Systems Under Heavy-Tailed Noise. - Vinay Kanakeri; Aritra Mitra (CoRR, 2025)