Nancy Pollard
Robotics Institute / Computer Science Department
Carnegie Mellon University
About Professor Nancy Pollard
Professor Nancy Pollard is a distinguished faculty member at Carnegie Mellon University, a globally recognized leader in computer science and robotics. As a Professor in both the Robotics Institute and the Computer Science Department, she contributes to an environment celebrated for its pioneering research and innovative spirit. Carnegie Mellon University's Robotics Institute is consistently ranked among the top programs worldwide, known for its groundbreaking contributions to autonomous systems, AI, and human-robot interaction. This robust academic setting provides an unparalleled foundation for advancing the complex challenges of modern robotics, attracting top-tier talent and fostering interdisciplinary collaboration across engineering, computer science, and beyond.
🧬Research Focus
Professor Pollard's research lies at the cutting edge of robotics, focusing on critical areas such as robot hands, grasping, dexterous manipulation, and soft robotics. Her work delves into contact modeling, human motion analysis, manipulation interfaces, and motion planning, with significant applications in humanoid robotics and biomechanics for robotics. She aims to decipher how humans achieve complex manipulation tasks, translating these insights into robust control strategies for robots. This research is pivotal for developing robots capable of intricate object handling, dynamic interaction with environments, and seamless collaboration with humans, promising breakthroughs in manufacturing, healthcare, and exploration. Her interdisciplinary approach drives innovation in both robotic capability and expressive digital character interaction.
🎓Student Fit & Career
Graduate students aspiring to push the boundaries of robotics will find an exceptional mentor in Professor Pollard. Her group seeks intellectually curious PhD students and researchers with strong backgrounds in robotics, computer science, control theory, biomechanics, or related fields. Ideal candidates possess strong analytical skills, a passion for solving complex physical interaction problems, and a desire to contribute to groundbreaking graduate research. Working under her academic mentorship prepares students for diverse and impactful career paths, including leading research roles in academia, advanced R&D positions in industry within robotics engineering, AI, and automation, or entrepreneurial ventures driving the next generation of robotic technologies.
Research Areas
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