An MCMC Based Course to Teaching Assistant Allocation. - Saurabh Kumar; Shana Moothedath; Prasanna Chaporkar; Madhu N. Belur (ICNCC, 2016)

Rapidly Mixing Markov Chain Monte Carlo Technique for Matching Problems with Global Utility Function. - Shana Moothedath; Prasanna Chaporkar; Madhu N. Belur (CoRR, 2017)

A Randomized Algorithm for Minimum Cost Constrained Input Selection for State Space Structural Controllability. - Shana Moothedath; Prasanna Chaporkar; Madhu N. Belur (ECC, 2018)

Multi-stage Dynamic Information Flow Tracking Game. - Shana Moothedath; Dinuka Sahabandu; Andrew Clark 001; Sangho Lee 001; Wenke Lee; Radha Poovendran (GameSec, 2018)

A Game Theoretic Approach for Dynamic Information Flow Tracking to Detect Multi-Stage Advanced Persistent Threats. - Shana Moothedath; Dinuka Sahabandu; Joey Allen; Andrew Clark 001; Linda Bushnell; Wenke Lee; Radha Poovendran (CoRR, 2018)

A Flow-Network-Based Polynomial-Time Approximation Algorithm for the Minimum Constrained Input Structural Controllability Problem. - Shana Moothedath; Prasanna Chaporkar; Madhu N. Belur (IEEE Trans. Autom. Control., 2018)

Minimum Cost Feedback Selection for Arbitrary Pole Placement in Structured Systems. - Shana Moothedath; Prasanna Chaporkar; Madhu N. Belur (IEEE Trans. Autom. Control., 2018)

Optimal Network Topology Design in Composite Systems with Constrained Neighbors for Structural Controllability. - Shana Moothedath; Prasanna Chaporkar; Aishwary Joshi (ACC, 2019)

A Game Theoretic Approach for Dynamic Information Flow Tracking with Conditional Branching. - Dinuka Sahabandu; Shana Moothedath; Linda Bushnell; Radha Poovendran; Joey Allen; Wenke Lee; Andrew Clark 001 (ACC, 2019)

Minimizing Inputs for Strong Structural Controllability. - Kumar Yashashwi; Shana Moothedath; Prasanna Chaporkar (ACC, 2019)

Learning Equilibria in Stochastic Information Flow Tracking Games with Partial Knowledge. - Shruti Misra; Shana Moothedath; Hossein Hosseini; Joey Allen; Linda Bushnell; Wenke Lee; Radha Poovendran (CDC, 2019)

Dynamic Information Flow Tracking Games for Simultaneous Detection of Multiple Attackers. - Dinuka Sahabandu; Shana Moothedath; Joey Allen; Andrew Clark 001; Linda Bushnell; Wenke Lee; Radha Poovendran (CDC, 2019)

Target Controllability of Structured Systems. - Shana Moothedath; Kumar Yashashwi; Prasanna Chaporkar; Madhu N. Belur (ECC, 2019)

Stochastic Dynamic Information Flow Tracking Game with Reinforcement Learning. - Dinuka Sahabandu; Shana Moothedath; Joey Allen; Linda Bushnell; Wenke Lee; Radha Poovendran (GameSec, 2019)

Optimal selection of essential interconnections for structural controllability in heterogeneous subsystems. - Shana Moothedath; Prasanna Chaporkar; Madhu N. Belur (Autom., 2019)

Approximating constrained minimum cost input-output selection for generic arbitrary pole placement in structured systems. - Shana Moothedath; Prasanna Chaporkar; Madhu N. Belur (Autom., 2019)

Sparsest Feedback Selection for Structurally Cyclic Systems With Dedicated Actuators and Sensors in Polynomial Time. - Shana Moothedath; Prasanna Chaporkar; Madhu N. Belur (IEEE Trans. Autom. Control., 2019)

Quickest Detection of Advanced Persistent Threats: A Semi-Markov Game Approach. - Dinuka Sahabandu; Joey Allen; Shana Moothedath; Linda Bushnell; Wenke Lee; Radha Poovendran (ICCPS, 2020)

A Multi-Agent Reinforcement Learning Approach for Dynamic Information Flow Tracking Games for Advanced Persistent Threats. - Dinuka Sahabandu; Shana Moothedath; Joey Allen; Linda Bushnell; Wenke Lee; Radha Poovendran (CoRR, 2020)

Minimum Cost Feedback Selection in Structured Systems: Hardness and Approximation Algorithm. - Aishwary Joshi; Shana Moothedath; Prasanna Chaporkar (IEEE Trans. Autom. Control., 2020)

A Game-Theoretic Approach for Dynamic Information Flow Tracking to Detect Multistage Advanced Persistent Threats. - Shana Moothedath; Dinuka Sahabandu; Joey Allen; Andrew Clark 001; Linda Bushnell; Wenke Lee; Radha Poovendran (IEEE Trans. Autom. Control., 2020)

Optimal Network Topology Design in Composite Systems for Structural Controllability. - Shana Moothedath; Prasanna Chaporkar; Madhu N. Belur (IEEE Trans. Control. Netw. Syst., 2020)

Feedback Robustness in Structured Closed-loop System. - RaviTeja Gundeti; Shana Moothedath; Prasanna Chaporkar (Eur. J. Control, 2021)

Fully Decentralized and Federated Low Rank Compressive Sensing. - Shana Moothedath; Namrata Vaswani (ACC, 2022)

Stochastic Conservative Contextual Linear Bandits. - Jiabin Lin; Xian Yeow Lee; Talukder Z. Jubery; Shana Moothedath; Soumik Sarkar; Baskar Ganapathysubramanian (CDC, 2022)

Dec-AltProjGDmin: Fully-Decentralized Alternating Projected Gradient Descent for Low Rank Column-wise Compressive Sensing. - Shana Moothedath; Namrata Vaswani (CDC, 2022)

Fully-Decentralized Alternating Projected Gradient Descent for Low Rank column-wise Compressive Sensing. - Shana Moothedath; Namrata Vaswani (CoRR, 2022)

Distributed Stochastic Bandit Learning with Context Distributions. - Jiabin Lin; Shana Moothedath (CoRR, 2022)

Fast Federated Low Rank Matrix Completion. - Ahmed Ali Abbasi; Shana Moothedath; Namrata Vaswani (Allerton, 2023)

Feature Selection in Distributed Stochastic Linear Bandits. - Jiabin Lin; Shana Moothedath (ACC, 2023)

Distributed Stochastic Bandit Learning with Delayed Context Observation. - Jiabin Lin; Shana Moothedath (ECC, 2023)

Distributed Stochastic Bandits with Hidden Contexts. - Jiabin Lin; Shana Moothedath (ECC, 2023)

Comparing Decentralized Gradient Descent Approaches and Guarantees. - Shana Moothedath; Namrata Vaswani (ICASSP, 2023)

Federated Stochastic Bandit Learning with Unobserved Context. - Jiabin Lin; Shana Moothedath (CoRR, 2023)

Minimal Input Structural Modifications for Strongly Structural Controllability. - Geethu Joseph; Shana Moothedath; Jiabin Lin (CDC, 2024)

Distributed Stochastic Contextual Bandits for Protein Drug Interaction. - Jiabin Lin; Karuna Anna Sajeevan; Bibek Acharya; Shana Moothedath; Ratul Chowdhury (ICASSP, 2024)

Decentralized Low Rank Matrix Recovery from Column-Wise Projections by Alternating GD and Minimization. - Shana Moothedath; Namrata Vaswani (ICASSP, 2024)

Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits. - Jiabin Lin; Shana Moothedath; Namrata Vaswani (ICML, 2024)

Federated Learning for Heterogeneous Bandits with Unobserved Contexts. - Jiabin Lin; Shana Moothedath (ISIT, 2024)

Fast and Sample-Efficient Relevance-Based Multi-Task Representation Learning. - Jiabin Lin; Shana Moothedath (IEEE Control. Syst. Lett., 2024)

Stochastic Dynamic Information Flow Tracking game using supervised learning for detecting advanced persistent threats. - Shana Moothedath; Dinuka Sahabandu; Joey Allen; Linda Bushnell; Wenke Lee; Radha Poovendran (Autom., 2024)

Thompson Sampling for Stochastic Bandits with Noisy Contexts: An Information-Theoretic Regret Analysis. - Sharu Theresa Jose; Shana Moothedath (Entropy, 2024)

Dynamic Information Flow Tracking for Detection of Advanced Persistent Threats: A Stochastic Game Approach. - Shana Moothedath; Dinuka Sahabandu; Joey Allen; Andrew Clark 001; Linda Bushnell; Wenke Lee; Radha Poovendran (IEEE Trans. Autom. Control., 2024)

RL-ARNE: A Reinforcement Learning Algorithm for Computing Average Reward Nash Equilibrium of Nonzero-Sum Stochastic Games. - Dinuka Sahabandu; Shana Moothedath; Joey Allen; Linda Bushnell; Wenke Lee; Radha Poovendran (IEEE Trans. Autom. Control., 2024)

Distributed Multi-Task Learning for Stochastic Bandits With Context Distribution and Stage-Wise Constraints. - Jiabin Lin; Shana Moothedath (IEEE Trans. Signal Inf. Process. over Networks, 2025)

Byzantine Resilient Federated Multi-Task Representation Learning. - Tuan Le; Shana Moothedath (CoRR, 2025)

Neural Contextual Bandits Under Delayed Feedback Constraints. - Mohammadali Moghimi; Sharu Theresa Jose; Shana Moothedath (CoRR, 2025)