I am an LLM Research Engineer, author, and educator focused on large language models, reasoning models, deep learning, and practical machine learning systems. My work centers on making modern AI easier to understand through clear explanations, working code, and end-to-end examples.

My background spans both academia and industry. I previously taught statistics and machine learning at the University of Wisconsin-Madison, and I have also worked in AI engineering roles in industry. Across both settings, the common thread in my work has been turning research ideas into tools, tutorials, and production-oriented workflows that practitioners can use.

Areas of Focus

• Large language models and reasoning models
• Pretraining, finetuning, inference, and evaluation
• PyTorch and performance-oriented AI engineering
• Machine learning education and technical writing

Best Places to Start

• Blog and notes
• Books
• Publications and research
• Machine Learning FAQ
• Talks and events
• Courses and teaching materials
• Software projects

Books and Resources

If you are mainly interested in hands-on LLM material, the best entry points are my Build a Large Language Model (From Scratch) book, my blog archive, and the accompanying open-source repositories linked throughout the site.

If you are looking for broader machine learning material, you may also find the Machine Learning FAQ, course pages, and resource archive useful.

Elsewhere

You can also find me on GitHub, LinkedIn, Google Scholar, and YouTube.

For speaking, collaboration, or professional inquiries, please use the details on the contact page.