Kyle R. Chickering’s Homepage

I am a recent PhD graduate in applied mathematics. I completed my dissertation under the supervision of Prof. Muhao Chen at UC Davis, where I was a member of the LUKA Lab. I am currently completing a research internship at the MBZUAI Institute of Foundation Models where I conduct research as part of the LLM pre-training team.

My research interests are roughly as follows:

1. How can we efficiently and effectively scale model training from small (< 100M params.) to large (1T+ params.) models?

2. Understanding the mathematical dynamics of training large models.

3. Using mathematics to understand how large models “think”.

4. Improving both the computational and statistical efficiency of ML training.

I was the founding research engineer at an R&D startup building efficient algorithms for generative vision models. I have worked in industry as a researcher and engineer building foundation models at scale for video and text.

I have previously worked in shock formation for analytic fluid mechanics (partial differential equations). Before that I was in software engineering working on (variously) data-center automation and classical computer vision.

🐙 GitHub

🔗 LinkedIn