Jesus Perez-Llano
Papers
1
Total Citations
2
H-Index
1
About
Dr. Jesus Perez-Llano stands at the forefront of an emerging interdisciplinary field, pioneering the integration of artificial intelligence with robotic neurosurgery. His most cited work, "Reinforcement Learning-Based Control for Collaborative Robotic Brain Retraction" (2024), addresses one of medicine's most formidable challenges: bringing AI safely into invasive surgical procedures. This research tackles the critical regulatory and safety hurdles that have historically prevented machine learning from assisting in delicate operations. By developing reinforcement learning frameworks that enable robots to collaborate with surgeons during brain retraction—a procedure requiring extreme precision—Dr. Perez-Llano is laying the groundwork for a new generation of semi-autonomous surgical assistants. His work bridges the gap between theoretical AI advances and the stringent demands of clinical practice, where algorithms must not only perform but also meet rigorous approval standards. Though still early in his career, his contributions are already shaping how researchers approach the safe deployment of AI in high-stakes medical environments. Dr. Perez-Llano's research promises to expand the boundaries of what is possible in robotic surgery, potentially making complex procedures safer and more accessible.
Research Focus
Key Achievements
Top Papers
- 1