Syeda Kulsoom Fatima

Sir Syed University of Engineering and Technology

Papers

Total Citations

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About

Syeda Kulsoom Fatima is a researcher at the forefront of applying deep learning to biomedical engineering, with a particular focus on computer vision for surgical robotics. Her most-cited work, "Object Recognition for Dental Instruments Using SSD-MobileNet" (2019, 22 citations), tackles a critical gap in robot-assisted surgery by developing a lightweight, real-time detection system specifically for dental instruments. This contribution is notable for its practical impact: by adapting the SSD-MobileNet architecture to the dental domain, Fatima’s work enables automated instrument tracking and identification, a key step toward making robotic assistance accessible for oral surgeons. Beyond this flagship paper, her research spans the intersection of artificial intelligence and healthcare, where she explores how efficient neural networks can enhance precision in medical procedures. Fatima’s work is distinguished by its focus on deployable, low-latency solutions—a crucial consideration for real-world surgical environments. With her research laying the groundwork for smarter, safer dental robotics, she is recognized as an emerging voice in the movement to democratize surgical technology, bridging the gap between advanced AI and everyday clinical practice.