Max Robotics — Global Service Robot Directory + US Certification

About

Mahsa Ghasemi’s research lies at the intersection of formal methods, robotics, and human-robot interaction, with a focus on making autonomous systems both verifiably correct and intuitively understandable. Her work addresses critical challenges in safety-critical autonomy, particularly in shared control and active perception. Ghasemi pioneered methods to translate complex counterexamples from formal verification—such as those generated for Markov decision processes—into structured natural language, bridging the gap between rigorous automated analysis and human comprehension. She also developed online active perception strategies for partially observable Markov decision processes under limited budgets, enabling agents to dynamically select information sources without prior knowledge. In the domain of safe human-robot shared autonomy, Ghasemi introduced a barrier pair method that formally guarantees safety even when a human operator’s actions may be unpredictable. Her contributions have been recognized with citations across these foundational topics, and her work on explainable counterexamples and safety-guaranteed shared control represents a notable step toward trustworthy, deployable robotic systems.