🚀 High Performance Computing (HPC) Researcher focused on large-scale FEM, sparse systems, and distributed compute. I build systems that don’t fit in RAM—and then make them faster anyway.

A modular, performance-first C++17 utility library designed for scientific computing and HPC workflows.

Core Capabilities

• Thread-safe logging (low overhead, multi-thread aware)
• Scope-based timing + profiling instrumentation
• Throughput benchmarking (compute + memory)
• Resource tracking (memory, execution, scaling)
• Built for MPI/OpenMP environments
• Clean integration with Meson build system

Designed to support real-world HPC workloads, not toy examples.

• Sparse Linear Algebra (CSR / COO / BSR / ELL / VBR)
• Krylov Subspace Methods (GMRES, iterative solvers)
• Finite Element Methods (MFEM)
• Adaptive Mesh Refinement (AMR)
• Distributed Systems & Multi-node Scaling
• Slurm-based HPC environments
• Memory-bound performance optimization

💡 Current emphasis: Bridging numerical methods with real-world scalability constraints (memory, bandwidth, communication overhead).

• Scaling FEM simulations to millions–billions of DOFs
• Sparse matrix performance tradeoffs
• MPI + OpenMP hybrid parallelism
• HPC profiling, bottlenecks, and memory diagnostics
• Linux-based research environments

• 💼 LinkedIn
• 🌍 Personal Site

Started in Manufacturing Engineering → pivoted into High Performance Computing, numerical methods, and large-scale simulation.

• C++ (Modern + Legacy) — 9
• C — 9
• Java (Spring Boot) — 8
• Assembly — 5

Strong focus on performance-critical, low-level systems

• MPI / OpenMP — 8
• MFEM / FEM pipelines — 7
• Slurm / Cluster tooling — 7

• TypeScript / React / Node — 8
• HTML / CSS — 8–9
• SQL (Postgres) — 8

• Shell (Linux) — 6
• Python — 4 (used pragmatically, not religiously)
• R — 4

• Odin
• Zig

• Ladder Logic (Allen-Bradley PLCs)
• CNC Programming (G/M Code)
• NodeJS, Cypress SDET
• C++ on Large Clusters

If your program fits in RAM, you’re playing a different game.

I focus on:

• Problems where memory is the bottleneck
• Systems where performance = survival
• Code that runs on clusters, not laptops