collaborators

9 papers

cs.CR2026

Federated Cybersecurity Testbed as a Service (FCTaaS): A framework to federate cybersecurity testbeds

Josh Dean, Yu-Zheng Lin, John Paul Martin Encinas +9

Rapid technological change is reshaping society through emerging domains such as autonomous vehicles and smart manufacturing, creating new research challenges in system design, ope…

cs.RO2026

Mission-Level Runtime Assurance Framework for Autonomous Driving

Chieh Tsai, Salim Hariri

This paper studies runtime safety for autonomous driving when high-level driving commands become faulty or unreliable. Unlike conventional runtime-safety approaches that mainly foc…

eess.SY2026

Online Reinforcement Learning for Safe Gain Scheduling in Nonlinear Quadrotor Control

Muhammad Junayed Hasan Zahed, Chieh Tsai, Salim Hariri +1

This paper presents an online reinforcement-learning framework for safe gain scheduling of a nonlinear quadcopter controller. Rather than learning thrust and torque commands direct…

cs.RO2026

RACF: A Resilient Autonomous Car Framework with Object Distance Correction

Chieh Tsai, Hossein Rastgoftar, Salim Hariri

Autonomous vehicles are increasingly deployed in safety-critical applications, where sensing failures or cyberphysical attacks can lead to unsafe operations resulting in human loss…

cs.CR2026

Security and Resilience in Autonomous Vehicles: A Proactive Design Approach

Chieh Tsai, Murad Mehrab Abrar, Salim Hariri

Autonomous vehicles (AVs) promise efficient, clean and cost-effective transportation systems, but their reliance on sensors, wireless communications, and decision-making systems ma…

eess.SY2026

Learning over Forward-Invariant Policy Classes: Reinforcement Learning without Safety Concerns

Chieh Tsai, Muhammad Junayed Hasan Zahed, Salim Hariri +1

This paper proposes a safe reinforcement learning (RL) framework based on forward-invariance-induced action-space design. The control problem is cast as a Markov decision process,…