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About

Jessica Villalobos is a robotics and human-robot interaction researcher whose work spans gesture-based control systems, robotic kinematics, and engineering education. Her most influential contribution, a 2017 framework for gesture-based robot control using wearable devices (45 citations), established foundational design principles for intuitive human-robot interfaces and rigorously evaluated their performance with human participants — helping to legitimize wearable gesture control as a viable paradigm in the field. She has also made significant technical contributions to robotic arm kinematics, developing comprehensive inverse kinematic solutions for 6-DOF UR/TM-type robots (23 citations) and conducting systematic statistical comparisons of competing IK methodologies for the widely used UR5 manipulator. Her 2019 exploration of human-inspired learning behavior in human-robot interaction (11 citations) reflects her broader interest in bridging cognitive science with robotics design. More recently, Villalobos has turned her attention to robotics education, developing virtual SCARA robot simulations aligned with Industry 4.0 and digital twin concepts, demonstrating a commitment to translating advanced research into accessible learning tools. Across her career, her work collectively exceeds 90 citations, marking her as a meaningful contributor to applied robotics research.