Siti Sabariah Abas
Papers
1
Total Citations
7
H-Index
1
About
Dr. Siti Sabariah Abas is a leading figure in optimization theory and its real-world applications, with a particular focus on conjugate gradient methods for unconstrained optimization. Her most cited work introduces a novel three-term conjugate gradient method that significantly improves convergence properties, demonstrating its practical utility in portfolio selection and robotic motion control. This 2021 paper has already garnered 7 citations, reflecting its growing influence in both theoretical and applied mathematics. Dr. Abas’s contributions bridge the gap between abstract algorithmic development and tangible engineering and financial challenges, offering efficient solutions for complex, high-dimensional problems. Her research is characterized by rigorous mathematical analysis and a clear commitment to solving practical problems, making her work valuable for students and researchers in optimization, robotics, and computational finance. Through her innovative approaches, Dr. Abas continues to advance the field, providing tools that enhance decision-making and control in dynamic systems.
Research Focus
Key Achievements
Top Papers
- 1