Mobile Robot-Assisted Cellular Environment Coverage. - Georgios Siamantas; Konstantinos Gatsis; Anthony Tzes (AIAI, 2010)

Power-aware communication for wireless sensor-actuator systems. - Konstantinos Gatsis; Miroslav Pajic; Alejandro Ribeiro; George J. Pappas (CDC, 2013)

Opportunistic sensor scheduling in wireless control systems. - Konstantinos Gatsis; Miroslav Pajic; Alejandro Ribeiro; George J. Pappas (CDC, 2014)

Opportunistic scheduling of control tasks over shared wireless channels. - Konstantinos Gatsis; Miroslav Pajic; Alejandro Ribeiro; George J. Pappas (ICCPS, 2014)

Optimal Power Management in Wireless Control Systems. - Konstantinos Gatsis; Alejandro Ribeiro; George J. Pappas (IEEE Trans. Autom. Control., 2014)

Value of forecasts in planning under uncertainty. - Konstantinos Gatsis; Ufuk Topcu; George J. Pappas (ACC, 2015)

Control with random access wireless sensors. - Konstantinos Gatsis; Alejandro Ribeiro; George J. Pappas (CDC, 2015)

Opportunistic Control Over Shared Wireless Channels. - Konstantinos Gatsis; Miroslav Pajic; Alejandro Ribeiro; George J. Pappas (IEEE Trans. Autom. Control., 2015)

State-based communication design for wireless control systems. - Konstantinos Gatsis; Alejandro Ribeiro; George J. Pappas (CDC, 2016)

Privacy-aware quadratic optimization using partially homomorphic encryption. - Yasser Shoukry; Konstantinos Gatsis; Amr Al-Anwar 001; George J. Pappas; Sanjit A. Seshia; Mani B. Srivastava; Paulo Tabuada (CDC, 2016)

Control-Aware Random Access Communication. - Konstantinos Gatsis; Alejandro Ribeiro; George J. Pappas (ICCPS, 2016)

State Estimation with Secrecy against Eavesdroppers. - Anastasios Tsiamis; Konstantinos Gatsis; George J. Pappas (CoRR, 2016)

Privacy preserving cloud-based quadratic optimization. - Andreea B. Alexandru; Konstantinos Gatsis; George J. Pappas (Allerton, 2017)

State estimation codes for perfect secrecy. - Anastasios Tsiamis; Konstantinos Gatsis; George J. Pappas (CDC, 2017)

Resilient monotone submodular function maximization. - Vasileios Tzoumas; Konstantinos Gatsis; Ali Jadbabaie; George J. Pappas (CDC, 2017)

Battery management for control systems with energy harvesting sensors. - Nicholas J. Watkins; Konstantinos Gatsis; Cameron Nowzari; George J. Pappas (CDC, 2017)

Wireless Control for the IoT: Power, Spectrum, and Security Challenges: Poster Abstract. - Konstantinos Gatsis; George J. Pappas (IoTDI, 2017)

Learning in Non-Stationary Wireless Control Systems via Newton's Method. - Mark Eisen; Konstantinos Gatsis; George J. Pappas; Alejandro Ribeiro (ACC, 2018)

State-Secrecy Codes for Stable Systems. - Anastasios Tsiamis; Konstantinos Gatsis; George J. Pappas (ACC, 2018)

Scenario-Based Model Predictive Control for Energy Harvesting Actuators. - Nicholas J. Watkins; Konstantinos Gatsis; Manfred Morari; George J. Pappas (ACC, 2018)

Sample Complexity of Networked Control Systems Over Unknown Channels. - Konstantinos Gatsis; George J. Pappas (CDC, 2018)

An Information Matrix Approach for State Secrecy. - Anastasios Tsiamis; Konstantinos Gatsis; George J. Pappas (CDC, 2018)

Learning Statistically Accurate Resource Allocations in Non-Stationary Wireless Systems. - Mark Eisen; Konstantinos Gatsis; George J. Pappas; Alejandro Ribeiro (ICASSP, 2018)

Optimization of Switched Linear Systems Over Non-Stationary Wireless Channels. - Mark Eisen; Konstantinos Gatsis; George J. Pappas; Alejandro Ribeiro (SPAWC, 2018)

Random access design for wireless control systems. - Konstantinos Gatsis; Alejandro Ribeiro; George J. Pappas (Autom., 2018)

Control Aware Communication Design for Time Sensitive Wireless Systems. - Mark Eisen; Mohammad M. Rashid; Konstantinos Gatsis; Dave Cavalcanti 001; Nageen Himayat; Alejandro Ribeiro (ICASSP, 2019)

Optimal Resource Allocation in Wireless Control Systems via Deep Policy Gradient. - Vinícius Lima 002; Mark Eisen; Konstantinos Gatsis; Alejandro Ribeiro (CoRR, 2019)

Control Aware Radio Resource Allocation in Low Latency Wireless Control Systems. - Mark Eisen; Mohammad M. Rashid; Konstantinos Gatsis; Dave Cavalcanti 001; Nageen Himayat; Alejandro Ribeiro (IEEE Internet Things J., 2019)

Learning in Wireless Control Systems Over Nonstationary Channels. - Mark Eisen; Konstantinos Gatsis; George J. Pappas; Alejandro Ribeiro (IEEE Trans. Signal Process., 2019)

Resource Allocation in Wireless Control Systems via Deep Policy Gradient. - Vinícius Lima 002; Mark Eisen; Konstantinos Gatsis; Alejandro Ribeiro (SPAWC, 2020)

State-Secrecy Codes for Networked Linear Systems. - Anastasios Tsiamis; Konstantinos Gatsis; George J. Pappas (IEEE Trans. Autom. Control., 2020)

Adaptive Scheduling for Machine Learning Tasks over Networks. - Konstantinos Gatsis (ACC, 2021)

Linear Regression over Networks with Communication Guarantees. - Konstantinos Gatsis (L4DC, 2021)

Statistical learning for analysis of networked control systems over unknown channels. - Konstantinos Gatsis; George J. Pappas (Autom., 2021)

Federated Reinforcement Learning at the Edge. - Konstantinos Gatsis (CoRR, 2021)

Cloud-Based Quadratic Optimization With Partially Homomorphic Encryption. - Andreea B. Alexandru; Konstantinos Gatsis; Yasser Shoukry; Sanjit A. Seshia; Paulo Tabuada; George J. Pappas (IEEE Trans. Autom. Control., 2021)

Latency-Reliability Tradeoffs for State Estimation. - Konstantinos Gatsis; Hamed Hassani; George J. Pappas (IEEE Trans. Autom. Control., 2021)

Federated Reinforcement Learning at the Edge: Exploring the Learning-Communication Tradeoff. - Konstantinos Gatsis (ECC, 2022)

Learning Robust State Observers using Neural ODEs (longer version). - Keyan Miao; Konstantinos Gatsis (CoRR, 2022)

Model-Free design of control systems over wireless fading channels. - Vinícius Lima 002; Mark Eisen; Konstantinos Gatsis; Alejandro Ribeiro (Signal Process., 2022)

Age of Information in Random Access Channels. - Xingran Chen; Konstantinos Gatsis; Hamed Hassani; Shirin Saeedi Bidokhti (IEEE Trans. Inf. Theory, 2022)

Homomorphically Encrypted Gradient Descent Algorithms for Quadratic Programming. - André Bertolace; Konstantinos Gatsis; Kostas Margellos (CDC, 2023)

Scalable Forward Reachability Analysis of Multi-Agent Systems with Neural Network Controllers. - Oliver Gates; Matthew Newton; Konstantinos Gatsis (CDC, 2023)

Stable and Safe Reinforcement Learning via a Barrier-Lyapunov Actor-Critic Approach. - Liqun Zhao; Konstantinos Gatsis; Antonis Papachristodoulou (CDC, 2023)

Learning Robust State Observers using Neural ODEs. - Keyan Miao; Konstantinos Gatsis (L4DC, 2023)

A Barrier-Lyapunov Actor-Critic Reinforcement Learning Approach for Safe and Stable Control. - Liqun Zhao; Konstantinos Gatsis; Antonis Papachristodoulou (CoRR, 2023)

Robust optimization for adversarial learning with finite sample complexity guarantees. - André Bertolace; Konstantinos Gatsis; Kostas Margellos (CDC, 2024)

How Deep Do We Need: Accelerating Training and Inference of Neural ODEs via Control Perspective. - Keyan Miao; Konstantinos Gatsis (ICML, 2024)

Walking the Values in Bayesian Inverse Reinforcement Learning. - Ondrej Bajgar; Alessandro Abate; Konstantinos Gatsis; Michael A. Osborne (UAI, 2024)

Wireless control: Retrospective and open vistas. - Matthias Pezzutto; Subhrakanti Dey; Emanuele Garone; Konstantinos Gatsis; Karl Henrik Johansson; Luca Schenato 001 (Annu. Rev. Control., 2024)

NLBAC: A Neural Ordinary Differential Equations-based Framework for Stable and Safe Reinforcement Learning. - Liqun Zhao; Keyan Miao; Konstantinos Gatsis; Antonis Papachristodoulou (CoRR, 2024)

Opt-ODENet: Neural ODE Controller Design with Differentiable Optimization Layers for Safety and Stability. - Keyan Miao; Liqun Zhao; Han Wang 026; Konstantinos Gatsis; Antonis Papachristodoulou (L4DC, 2025)

NLBAC: A neural ODE-based algorithm for state-wise stable and safe reinforcement learning. - Liqun Zhao; Keyan Miao; Hongpeng Cao; Konstantinos Gatsis; Antonis Papachristodoulou (Neurocomputing, 2025)

Opt-ODENet: A Neural ODE Framework with Differentiable QP Layers for Safe and Stable Control Design (longer version). - Keyan Miao; Liqun Zhao; Han Wang 026; Konstantinos Gatsis; Antonis Papachristodoulou (CoRR, 2025)

PAC Apprenticeship Learning with Bayesian Active Inverse Reinforcement Learning. - Ondrej Bajgar; Dewi S. W. Gould; Jonathon Liu; Alessandro Abate; Konstantinos Gatsis; Michael A. Osborne (CoRR, 2025)