Papers
5
Total Citations
81
H-Index
4
About
Faraz Junejo is a multidisciplinary researcher whose work spans advanced control systems, robotics, medical imaging, and intelligent transportation. He is perhaps best recognized for his highly cited 2020 contribution on output feedback adaptive fractional-order super-twisting sliding mode control of robotic manipulators, which has garnered 58 citations and demonstrates his deep expertise in developing sophisticated, robust control strategies for complex mechanical systems. His early work in medical robotics, including an X-ray-based machine vision system for distal locking of intramedullary nails, reflects a commitment to applying engineering precision to critical surgical challenges. Junejo has also made meaningful contributions to practical robotics design, developing cost-effective painting robots tailored for industrial contexts in developing economies and a remotely operated surveillance robot capable of live video streaming. More recently, his research has extended into artificial intelligence applications within intelligent transportation systems, signaling a forward-looking engagement with emerging technologies. Across his career, Junejo demonstrates a rare breadth — bridging theoretical control engineering with real-world applications in healthcare, industry, and infrastructure — making his work particularly valuable for students and researchers seeking innovative, application-driven engineering solutions.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3RoboCop; A Robust Surveillance Robot6 citations · 2018
- 4Computer Aided Design of a Low-Cost Painting Robot5 citations · 2017
- 5