About Me

Hey there! I’m Ben Wyatt. I graduated from the University of Rochester in 2023 with a BS in Physics and BA in Economics.

Academic & Research Experience

During my internship at Los Alamos National Laboratory, I conducted data science work in Python for an experiment at the OMEGA‐EP laser facility. The project used very short, intense laser pulses to strike thin film targets, producing fast‐moving proton beams. Our goal was to evaluate how effectively these beams could be used for imaging. Laser-driven proton radiography can penetrate dense materials and capture rapid changes in high‐pressure, high‐temperature environments, making it valuable for studying fusion experiments and other extreme physics scenarios. Here’s the published paper.

Current Role

I’m currently at EY working as an AI Engineer in New York City. My team is focused on training LLMs for specific internal tasks. I’ve built end-to-end training pipelines for Supervised Finetuning, Continuous Pretraining, and Model Distillation. Most of the grunt work is in the data preparation. I’m also heavily focused on various Synthetic Data Generation techniques, especially multi-page long-context documents.

I’ve also been involved on the infrastructure side, managing the kubernetes deployment on a 16 H200 cluster.

On the application end, I’m a big proponent of the declarative agent framework DSPy.

Some general thoughts about Generative AI

Hobbies and Interests

I’ve recently become obsessed with Obsidian for note taking and writing.

I play the guitar and listen to music. Here are some artists I’ve been listening to recently:

I’m really interested in building great knowledge accumulation systems that enable curiosity-driven learning. I like to curate my Substack and RSS feeds. As well as YouTube videos and podcasts. I’ve only recently come around to the utility of Twitter. I see LLMs as a powerful force for this type of curiosity-driven learning and I’m really excited to see what next-generation tools look like.

Get in Touch