Danish Masood

Papers

Total Citations

H-Index

About

Danish Masood is a leading researcher at the intersection of surgical robotics and intelligent sensing systems. His work primarily focuses on advancing opto-mechatronic technologies for medical applications, with key contributions in fiber-optic-based force and shape sensing for surgical robots. In his highly cited 2023 review, Masood systematically analyzed the role of optic signals in optimizing robotic system performance, establishing a foundational framework for integrating fiber-optic sensors into next-generation surgical tools. This work has garnered 28 citations, reflecting its importance in guiding both academic research and clinical device development. Additionally, Masood has pioneered novel approaches in biomedical imaging and localization, as demonstrated by his 2022 study on 3D hand acupoint localization using RGB-D CNN fusion. By combining hand geometry with landmark detection, he achieved precise, non-invasive targeting for acupuncture applications—a breakthrough that has earned 20 citations. His interdisciplinary methodology bridges computer vision, deep learning, and traditional medicine, showcasing his ability to solve complex real-world problems. Masood’s research not only advances surgical precision and patient safety but also opens new avenues for human-robot interaction and therapeutic robotics. His work continues to inspire innovations in smart medical devices and intelligent sensing.