K. Arulmozhi

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About

Dr. K. Arulmozhi is a distinguished researcher in the fields of multiple attribute decision-making (MADM), fuzzy set theory, and medical robotics. Her work focuses on developing novel Pythagorean vague normal operators that enhance the precision and reliability of decision-making processes in complex, uncertain environments. Her most cited paper, "Multiple attribute decision-making Pythagorean vague normal operators and their applications for the medical robots process on surgical system" (2023, 7 citations), introduces groundbreaking computational models that optimize robotic surgical system performance by integrating vague set theory with Pythagorean fuzzy logic. This contribution is pivotal for advancing autonomous decision-making in healthcare, particularly in high-stakes surgical settings where accuracy is critical. Dr. Arulmozhi’s research bridges theoretical mathematics and practical engineering, offering robust frameworks for evaluating and selecting optimal robotic processes. Her work has garnered attention for its potential to improve patient outcomes and operational efficiency in medical robotics. With a growing citation record, she is establishing herself as a key voice in the intersection of fuzzy decision science and biomedical engineering, inspiring future innovations in intelligent surgical systems.