Wiyada Kumam

About

Wiyada Kumam is a leading figure in applied mathematics and optimization, renowned for developing advanced iterative methods to solve complex nonlinear systems. Her primary research focuses on derivative-free algorithms, spectral conjugate gradient techniques, and the innovative use of inertial effects to accelerate convergence in monotone nonlinear equations. Kumam’s major contributions include proposing two hybrid spectral methods with inertial effects for solving systems of nonlinear equations with convex constraints, directly impacting fields like robotics and image restoration. Her most cited work, an inertial-based derivative-free method from 2020, has garnered 30 citations, while her 2021 hybrid spectral paper has 23 citations, underscoring their influence. Beyond numerical analysis, she explores fuzzy set theory, applying comparison measures for Pythagorean m-polar fuzzy sets to robotics and movie recommender systems. With papers published as recently as 2024, Kumam continues to bridge theoretical optimization and real-world applications, making her work essential for researchers tackling nonlinear problems in engineering and artificial intelligence.

Research Focus

Key Achievements

Top Papers

1. 1
   Inertial-Based Derivative-Free Method for System of Monotone Nonlinear Equations and Application

   30 citations · 2020
2. 2
   Two Hybrid Spectral Methods With Inertial Effect for Solving System of Nonlinear Monotone Equations With Application in Robotics

   23 citations · 2021
3. 3
   Some combined techniques of spectral conjugate gradient methods with applications to robotic and image restoration models

   7 citations · 2024
4. 4
   Comparison measures for Pythagorean $ m $-polar fuzzy sets and their applications to robotics and movie recommender system

   6 citations · 2023

Key Collaborators

Contact & Links