Papers
4
Total Citations
9
H-Index
2
About
Faraz Lotfi is a robotics researcher whose work spans autonomous off-road navigation, underwater tracking, and surgical skill assessment. His 2025 paper on topological mapping for traversability-aware long-range navigation in off-road terrain (3 citations) introduces a method for robots to plan and explore unstructured environments like forests without relying on predefined pathways—a critical advance for field robotics. In underwater robotics, Lotfi developed a robust diver tracking and recovery system using YOLOv7 and SORT with spiral search (2023, 3 citations), addressing the six-degree-of-freedom challenge of tracking targets in visually degraded aquatic environments. His work in medical robotics includes a computational framework for surgical skill assessment (2021, 2 citations), using kinematic data to automate evaluation of suturing tasks in robotic-assisted minimally invasive surgery, reducing expert surgeons' manual feedback burden. Most recently, Lotfi has explored constrained robotic navigation using large language models and speech instructions (2024, 1 citation), leveraging adverbs to enable intuitive human-robot interaction. Though early in his career, Lotfi’s research demonstrates remarkable breadth—from forest trails to ocean depths to operating rooms—and his interdisciplinary approach positions him as a rising figure in autonomous systems and human-robot interaction.
Research Focus
Key Achievements
Top Papers
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