Parallel programming & HPC
Performance, scalability and energy efficiency in multicore and distributed-memory systems; PGAS, Unified Parallel C (UPC), UPC++, MPI and OpenMP.
Computer scientist with a PhD focused on high-performance computing (HPC), parallel programming and the PGAS programming model. I work across scientific computing, software development and self-hosted infrastructure.
I enjoy understanding systems end to end: from algorithms, memory movement and parallel execution to the services, automation and observability that make software useful in practice.

My profile combines a research background in parallel computing with practical software engineering and Linux-based service operations. The sections below distinguish published research from independent and home-lab projects.
Performance, scalability and energy efficiency in multicore and distributed-memory systems; PGAS, Unified Parallel C (UPC), UPC++, MPI and OpenMP.
Self-hosted applications deployed with Docker Compose and Portainer, routed through Traefik, with monitoring, logging and security controls.
Work spanning C/C++ parallel code, Python tooling, PHP/web applications, shell automation and practical service integration.
Personal infrastructure for media, collaboration, document workflows, backups, observability and local AI experimentation.
My doctoral work, completed at the University of Oslo with Simula Research Laboratory, examined the PGAS programming model and mesh-based computation. The associated papers investigate energy efficiency and performance, optimization of fine-grained irregular communication in UPC, and a comparison of UPC and UPC++.
For professional collaboration, research discussion or software engineering opportunities: