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About

Hiya Roy is a leading researcher in autonomous space exploration, specializing in machine learning for planetary rover systems. Her most impactful work, "MAARS: Machine Learning-based Analytics for Automated Rover Systems" (2020, 29 citations), introduces a groundbreaking framework that integrates advanced AI into rover navigation and decision-making for Mars, Moon, and beyond. This research directly addresses the challenge of enabling real-time, self-driving capabilities in extreme off-world environments, leveraging the High Performance Spaceflight Computing (HPSC) initiative. Roy’s contributions are pivotal in bridging terrestrial AI advances with spaceflight constraints, significantly enhancing rover autonomy and scientific data collection efficiency. Her work has garnered attention for its potential to revolutionize how future missions explore distant terrains, reducing reliance on Earth-based commands. With a growing citation record, Roy is recognized as a key innovator at the intersection of robotics, machine learning, and aerospace engineering, inspiring students and researchers to push the boundaries of intelligent space systems.