Abdulkarim Hassan Ibrahim
King Mongkut's University of Technology Thonburi, King Fahd University of Petroleum and Minerals
Papers
2
Total Citations
68
H-Index
2
About
Abdulkarim Hassan Ibrahim is a rising figure in numerical optimization, whose work focuses on developing efficient algorithms for solving unconstrained optimization problems with real-world applications. His primary research areas include conjugate gradient methods, motion control, and image recovery. Ibrahim’s major contribution lies in designing hybrid conjugate gradient algorithms that combine the strengths of classical methods—such as Hestenes-Stiefel (HS) and Liu-Storey (LS)—to achieve faster convergence and improved stability. His 2021 paper on a hybrid conjugate gradient approach for unconstrained optimization and motion control has garnered 51 citations, reflecting its impact on both theoretical and applied domains. Building on this, his 2023 work introduced an HS-LS hybrid algorithm that extends these techniques to image recovery, demonstrating versatility across engineering and computational imaging. Ibrahim’s research is notable for bridging algorithmic innovation with practical problem-solving, offering robust tools for motion control systems and signal processing. With a growing citation record and a focus on high-impact applications, he is establishing himself as a key contributor to modern optimization methods, inspiring further exploration in hybrid algorithm design.
Research Focus
Key Achievements
Top Papers
- 1
- 2