Jesus Moncada-Ramirez
Papers
2
Total Citations
16
H-Index
2
About
Jesus Moncada-Ramirez is a rising researcher at the intersection of robotics and artificial intelligence, whose work focuses on enhancing the reasoning capabilities of autonomous systems. His primary research areas include large language model (LLM) integration in robotics, semantic scene understanding, and agentic workflow design for object-centered planning. Moncada-Ramirez’s major contribution lies in developing novel agentic workflows that mitigate the critical problem of hallucination in LLMs when applied to robotic tasks. By pairing LLMs with semantically rich representations like semantic maps, his work enables robots to more accurately interpret and reason about their workspace, improving decision-making in complex environments. His most cited paper, "Agentic Workflows for Improving Large Language Model Reasoning in Robotic Object-Centered Planning" (2025), has already garnered 13 citations, signaling strong early impact in this rapidly evolving field. This foundational work, along with a closely related follow-up study, demonstrates his ability to address pressing challenges in trustworthy AI for robotics. Moncada-Ramirez’s research is particularly notable for bridging the gap between high-level cognitive reasoning and low-level robotic control, offering practical solutions for more reliable and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
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