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About

Luis A. Pineda is a leading researcher in robotics and artificial intelligence, whose work spans multimodal perception, human-robot interaction, and cognitive architectures for service robots. His most cited paper, "NeuralFeels with neural fields: Visuotactile perception for in-hand manipulation" (2024, 66 citations), introduces a groundbreaking framework that fuses visual and tactile sensing to enable robots to estimate object pose and shape during dexterous in-hand manipulation—a critical step toward human-level robotic dexterity. Pineda has also made significant contributions to social robotics, exploring how robotic facial expressions of anger (2019, 37 citations) can influence collaborative interactions, and developing the SitLog programming language (2013, 22 citations) for declarative task specification in service robots. His work on "Equi-Reward Utility Maximizing Design" (2017, 22 citations) addresses optimal environmental redesign for human-robot cooperation, while his research on continual planning for search and rescue robots (2015, 18 citations) advances autonomous emergency response. With over 220 total citations across his ten most-cited papers, Pineda’s integrated approach—combining perception, reasoning, and affective computing—positions him as a key figure in creating robots that can perceive, reason, and interact naturally in complex, real-world environments.