Rachel Holladay
Mechanical Engineering and Applied Mechanics (MEAM)
University of Pennsylvania
About Professor Rachel Holladay
The University of Pennsylvania's Department of Mechanical Engineering and Applied Mechanics (MEAM) stands as a beacon of innovation and academic excellence within a top-tier institution renowned for its interdisciplinary engineering research. With a rich history of groundbreaking contributions, MEAM provides a dynamic environment where fundamental scientific inquiry meets practical application, attracting leading scholars and fostering an unparalleled academic atmosphere. It is within this distinguished setting that Rachel Holladay serves as the Asness Family Foundation Assistant Professor, playing a pivotal role in advancing the department’s strengths in robotics and autonomous systems. Her appointment highlights Penn's commitment to nurturing cutting-edge research and leadership in complex engineering challenges.
🧬Research Focus
Professor Holladay's research in robotics and autonomous systems focuses intensely on robot manipulation, tackling the intricate challenges of long-horizon planning and contact-rich manipulation. Her work pushes the boundaries of motion planning and task and motion planning, developing robust uncertainty-aware control strategies essential for robots operating in unpredictable real-world environments. By addressing the complex interplay of discrete and continuous decision-making, physical constraints, and partial information, her Autonomous Manipulation @ Penn (AMP) Lab aims to enable robots to perform extended sequences of actions crucial for applications ranging from household assistance and medical logistics to classroom organization. This foundational robotics research promises to unlock new capabilities, leading to significant breakthroughs in artificial intelligence and autonomous system functionality.
🎓Student Fit & Career
Students aspiring to undertake graduate research under Professor Holladay's academic mentorship will find an intellectually rigorous and highly collaborative environment. Ideal PhD students possess a strong background in robotics, computer science, control systems, or mechanical engineering, coupled with an eagerness to tackle complex, real-world problems. They should be innovative thinkers with excellent analytical and programming skills, comfortable working at the intersection of theory and practical implementation. Graduates from her lab are well-prepared for impactful careers in academia, industrial research and development within robotics and AI, or leadership roles in companies developing advanced autonomous systems, contributing to the next generation of intelligent machines.
Research Areas
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