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About

Kaijen Hsiao is a prominent robotics researcher whose work sits at the intersection of robotic manipulation, tactile sensing, and assistive technology. Her research has fundamentally advanced how robots perceive, grasp, and interact with objects in unstructured, real-world environments — challenges that remain central to practical robot deployment. Her most celebrated contribution, "Human-Inspired Robotic Grasp Control With Tactile Sensing" (2011, 410 citations), introduced a biologically motivated control framework enabling robots to handle unknown objects with remarkable delicacy. This work helped establish tactile sensing as a critical component of reliable grasping systems. Complementing this, her planning-under-uncertainty research — including "Grasping POMDPs" (2007, 157 citations) — demonstrated how probabilistic decision-making frameworks could be applied to manipulation tasks. Hsiao has also made significant contributions to assistive robotics, most notably through "Robots for Humanity" (2013, 159 citations), which explored how mobile manipulators could restore independence to people with disabilities. Her work on human-in-the-loop systems and robot learning from demonstration further reflects her commitment to making robots genuinely useful to people. With over 1,500 cumulative citations, Hsiao's research has meaningfully shaped modern mobile manipulation and human-robot collaboration.