Safdar Mahmood

Brandenburg University of Technology Cottbus-Senftenberg

Papers

Total Citations

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About

Safdar Mahmood is a researcher at the forefront of applying artificial intelligence and robotics to critical humanitarian and healthcare challenges. His work centers on three key areas: autonomous systems for assisted living, FPGA-accelerated deep learning, and robotic manipulation for medical applications. Mahmood’s most impactful contribution is the development of a deep neural network system for detecting improvised landmines using Ground Penetrating Radar (GPR) imagery, optimized for deployment on FPGAs—a project that has earned 7 citations and addresses a life-saving need in post-conflict zones. He has also pioneered the design of assistive robots for elderly care, a field that gained renewed urgency during the COVID-19 pandemic, and created "InjectMeAI," an autonomous injection humanoid aimed at reducing human-to-human contact in healthcare settings. His work on an HLS-based framework for articulated robot inverse kinematics further demonstrates his expertise in bridging software and hardware for real-time robotic control. With a growing citation record and a clear focus on tangible, socially impactful applications, Mahmood is establishing himself as a researcher whose innovations directly improve safety and quality of life.