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Rachel Holladay
Incoming Asst Professor
University of Pennsylvania
rhollada [at] seas.upenn.edu
Pronouns: she/her

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I am an incoming Assistant Professor in the Mechanical Engineering and Applied Mechanics (MEAM) Department at the University of Pennsylvania, starting in Fall 2025. I will be the Asness Family Foundation Assistant Professor of Mechanical Engineering and will be a member of the General Robotics, Automation, Sensing & Perception (GRASP) lab.

My research focuses on enabling robots to robustly perform long-horizon, contact-rich manipulation tasks in everyday environments. I envision a world in which robots are cooking dinner at home, packing supplies in hospitals and cleaning up messy classrooms. Completing these types of tasks requires a robot to execute long sequences of actions, where each action involves many connected, discrete and continuous choices that are critically impacted by physical constraints. Furthermore, for robots to operate in the real world, it is critical that they be able to cope with partial or uncertain information. To solves these types of tasks, my research proposes models and algorithms that exploit the physics and geometry of the world in order to tackle the dual challenges of long-horizon decision-making and acting under uncertainty. I contribute models based on engineering mechanics and learned from data and I build on tools from motion planning, control and task planning.

Currently I am a Postdoctoral Researcher in MEAM at UPenn, working with Cynthia Sung and Daniel Koditschek. Previously, I completed a Ph.D. (2024) in Electrical Engineering and Computer Science at MIT, advised by Tomás Lozano-Pérez and Alberto Rodriguez. At MIT I was a member of the LIS Group and the MCube Lab. Prior to MIT, I received a B.S. (2017) in Computer Science and Robotics from CMU.

I am recruiting students for a Fall 2025 start date! If you're interested, please visit the GRASP Lab website for information about the PhD and Master's application process and, within the application, please be sure to mention my name.

Miscellaneous. My academic lineage is more of a "family graph" than a "family tree".



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