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"I don't sell promises, I sell guarantees." - NF (2025) I am the Shalini and Rajeev Misra Presidential Assistant Professor in the Mechanical Engineering and Applied Mechanics (MEAM) Department at the University of Pennsylvania. I hold secondary appointments in the departments of Computer and Information Science (CIS) and Electrical and Systems Engineering (ESE) and I am a core faculty at the General Robotics, Automation, Sensing & Perception (GRASP) lab. Before joining Penn, I was a Postdoctoral Associate in the Interactive Robotics Group of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT), advised by Prof. Julie A. Shah. I obtained a Ph.D. in Robotics, Control and Intelligent Systems from the Swiss Federal Institute of Technology in Lausanne (EPFL), advised by Prof. Aude Billard. Prior to this, I spent time as a Research Assistant in the Robotics and Mechatronics Institute at the German Aerospace Center (DLR) and at NYU Abu Dhabi. I hold a B.Sc. in Mechatronics from Monterrey Tech and M.Sc. in Automation and Robotics from TU Dortmund. Email • LinkedIn • CV • Short Bio • Google Scholar |
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Established in Fall 2022. The goal of my research is to study and develop the physical and perceptual adaptive intelligence necessary for robots to learn from and interact with humans, while being able to adapt to a wide-range of human capabilities, needs and ever-changing environments achieving fluid human-robot collaborative autonomy; i.e., when humans and robots collaborate harmoniously. We focus on applications where such fluid collaboration is necessary or safety critical, such as teaching robots cumbersome dexterous manipulation tasks with minimal human effort, navigating swiftly and safely in busy human-centric spaces, physically assisting humans in heavy work and contact-rich activities, physical therapy and rehabilitation. We tackle these problems by developing novel and tightly coupled learning, control and estimation algorithms that enjoy from stability, safety, efficiency and robustness guarantees. This involves research at the intersection of machine learning, control theory, artificial intelligence, perception, biomechanics and psychology - with a physical human-robot interaction perspective. A summary of our contributions in these research directions over the past three years at Penn can be found in my most recent research statement (12/24) . Figueroa Lab Github • Figueroa Lab Youtube Channel • Prof. Figueroa's PhD Thesis • Textbook on "Learning for Adaptive and Reactive Robot Control: A DS Approach" |
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