About me

I'm Alpha, a machine learning engineer who likes building things that are equal parts ambitious and grounded.

Most of my work lives at the intersection of multimodality and accelerated computing, teaching models to read images and text together, and getting them to train fast on whatever silicon is in front of me, whether that's an H100, a TPU pod, or AWS Trainium. My thesis on a vision-language model reached 92% accuracy, and a Google Cloud TPU Research Cloud grant of $376,000 let me push those experiments further than a student budget normally allows.

These days a lot of that work runs under two sibling research labs I founded: Experimental Machines, which benchmarks GPUs, NPUs and ASICs from the datacenter down to the phone, and Experimental Intelligence, which trains small models from scratch and labels its own data. Both publish the code, logs and raw numbers so every claim can be rerun.

What I care about beyond the benchmarks is teaching. I've given 25+ talks, from PyTorch Conference Europe to community rooms across the Philippines, because the moment something clicks for someone in the audience is genuinely my favorite part of this field. As a GitHub Campus Expert, a lot of that has meant helping other students take their first commit, run their first model, and realize the tools are not as scary as they look.

When I'm not training models or making slides, I'm usually reading about where this is all heading, and trying to build a small part of that future myself.