Ngan

My Story

Over a decade ago, I started my journey in the world of computing with nothing but curiosity and a determination to understand how machines think. From those humble beginnings — debugging low-level code on borrowed hardware — I discovered a deep passion for pushing computational boundaries. That spark led me into High-Performance Computing, where I learned to harness the raw power of GPUs, parallel architectures, and distributed systems.

Along the way, I wore many hats just to make ends meet — and each one taught me something invaluable. I started as an undergraduate studying Theoretical Physics and Computational Physics, which gave me a rigorous foundation in mathematical modeling and scientific thinking. That led to research in molecular dynamics, where I ran simulations on HPC clusters to model potential drug candidates for other labs. From there, I pivoted to embedded systems engineering, building hands-on STEM projects that brought science to life for kids. I then moved into semiconductor manufacturing as a chip package developer, working directly on production lines. The pull of software eventually brought me into full-stack development, followed by mobile application development. Through every transition, I learned from books, conferences, colleagues, courses, forums, and above all, the vast and generous internet. In recent years, all of these threads have converged as I transitioned into my current focus as an AI Solution Orchestrator and AI Engineer.

As the AI revolution unfolded, I found myself at the intersection of HPC and machine learning — a place where performance engineering meets intelligent systems. Over 10+ years, I've designed and optimized AI pipelines that process massive datasets, built GPU-accelerated training infrastructure, and architected systems that scale from prototype to production. From CUDA kernel tuning to orchestrating multi-node training clusters, every challenge has deepened my understanding of what it takes to build AI systems that truly perform.

Today, I focus on AI Architecture — designing the backbone systems that make large-scale AI possible. I write about the lessons I've learned along the way: the tradeoffs, the failures, the breakthroughs, and the practical knowledge that only comes from years of hands-on engineering. This blog is my way of sharing that journey and helping others navigate the complex landscape of HPC and AI.

Skills & Expertise

Tools I Use

Currently Working On

Connect