Fundamentals
Core concepts in numerical methods, floating-point arithmetic, and computational mathematics foundations.
Content being enhancedHigh-Performance Scientific Computing
Developing sophisticated computational solutions for complex scientific and engineering challenges. With 15+ years of experience, I specialize in high-performance computing, numerical algorithms, and large-scale simulations that push the boundaries of computational science.
Numerical Methods
Advanced numerical algorithms for solving differential equations, linear algebra, optimization, and Monte Carlo simulations.
Parallel Computing
Multi-core, GPU, and distributed computing solutions using OpenMP, MPI, CUDA, and modern parallel programming paradigms.
Performance Optimization
Code profiling, algorithmic optimization, memory management, and scalability analysis for maximum computational efficiency.
Advanced Techniques
Sophisticated algorithms for partial differential equations, finite element methods, and computational fluid dynamics.
Content being enhancedProject Portfolio
High-impact scientific computing projects including simulations, modeling, and computational research.
Content being enhancedTools & Frameworks
Comprehensive overview of scientific computing tools, libraries, and high-performance computing platforms.
Content being enhancedTutorials & Examples
Practical tutorials on implementing numerical algorithms and optimizing computational performance.
Content being enhancedInterview Preparation
Technical interview preparation for scientific computing and high-performance computing roles.
Content being enhancedCore Competencies
Numerical Algorithms
- Linear algebra (BLAS, LAPACK, sparse methods)
- Ordinary and partial differential equations
- Optimization algorithms (gradient descent, genetic algorithms)
- Monte Carlo and quasi-Monte Carlo methods
- Finite element and finite difference methods
High-Performance Computing
- Parallel programming (OpenMP, MPI)
- GPU computing (CUDA, OpenCL)
- Distributed computing and cluster management
- Memory optimization and cache efficiency
- Scalability analysis and performance profiling
Programming Languages
- C/C++ for performance-critical applications
- Fortran for scientific legacy code
- Python (NumPy, SciPy, Numba)
- MATLAB for rapid prototyping
- Julia for modern scientific computing
Applications
- Computational fluid dynamics (CFD)
- Molecular dynamics and quantum simulations
- Climate and weather modeling
- Financial modeling and risk analysis
- Image processing and computer vision