Sam Foreman

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🔥 What I Work on

As a member of the AI / ML Group at ALCF, I work on:

• 🤖 🧪 AI + Science
• 🎲 Building better sampling methods for Lattice QCD
• 🧬 Genome-Scale Language Models
  • GenSLM
  • 🥇 ACM Gordon Bell Special Prize

• 🌍 Foundation models for long term climate forecasting
• 🏃‍♂️ Scaling Large Language Models
• 🏎️ Distributed training across thousands of GPUs

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📍 How I got here

My current research focuses on using deep generative modeling to help build better sampling algorithms in lattice gauge theory. In particular, I’m interested in building gauge equivariant neural network architectures and using inductive priors to incorporate physical symmetries into machine learning models.

I received my PhD in Physics from the University of Iowa in 2019 and my thesis was on Learning Better Physics: A Machine Learning Approach to Lattice Gauge Theory.

Prior to this, I completed two bachelors degrees (Engineering Physics and Applied Mathematics, 2015) at The University of Illinois at Urbana-Champaign. My undergraduate dissertation was titled Energy Storage in Quantum Resonators and was supervised by Professor Alfred Hübler within the Center for Complex Systems Research at UIUC.

This work ultimately resulted in a patent !!

Time Tracking

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📊 GitHub Stats

Even More !!

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