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About

Suzana Uran is a robotics and control systems researcher whose work spans telerobotics, autonomous systems, robot control theory, and human-robot collaboration. She first gained significant recognition with her pioneering 2001 paper on telerobotics experiments via the Internet (84 citations), which addressed the practical challenge of remotely training operators to work with expensive and safety-critical industrial equipment — a visionary contribution that anticipated today's remote operation paradigms. Her theoretical contributions include robust impedance control and sliding-mode neural network controllers for industrial robots, tackling the demanding problem of simultaneous motion tracking and force control during environmental contact. She has also advanced underactuated mechanism control and neural-network-based adaptive estimation for highly nonlinear robotic plants. Beyond classical control, Uran has made meaningful contributions to autonomous and rescue robotics, including model-based fault diagnosis for ROS-based systems, path-following algorithms for skid-steered mobile robots, and community-driven modular software development for search and rescue platforms. Her more recent work on LiDAR-based human-robot safety (2023) reflects a timely focus on collaborative robotics in industrial environments. With over 220 cumulative citations, her career represents a broad and sustained contribution to making robots more capable, reliable, and safe.