Engineering & Applied Mathematics
Numerical methods, optimization, systems modelling, and scientific computing.
Core Sub-topics & Research Themes
Convex & Non-Convex Optimization
Duality theory, KKT conditions, proximal gradient methods, interior-point algorithms, and ADMM decomposition.
Numerical Analysis & Linear Algebra
Condition numbers, Krylov subspace methods (GMRES, CG), QR/SVD factorizations, and floating-point error propagation.
Dynamical Systems & Non-Linear Control
Lyapunov stability, phase portraits, bifurcation analysis, state-space feedback, and model predictive control (MPC).
Finite Difference & Multi-Scale Modelling
Parabolic and hyperbolic PDE discretization, boundary value formulations, von Neumann stability, and spatial discretization.
Mathematical & Applied Methodologies
Scientific Computing Ecosystems
Symbolic-numeric modeling, high-precision ODE/PDE solvers, and automatic differentiation engines.
Convergence & Error Analysis
Rigorous bounding of truncation errors and algorithmic stability bounds.
Monographs & Publications in this Field
Numerical Methods & Systems Optimization
Engineering & Applied Mathematics Monograph · Series 03
Authors / Editorial Board: Algorism Press & CFSBR Faculty
- Convex optimization & gradient-based algorithms
- Dynamical systems modelling & stability analysis
- Finite-difference & numerical approximation techniques
Publishing in this Discipline
We welcome monograph and course-text proposals within this discipline. Every volume undergoes structural peer appraisal, code verification, and custom typographic design.