- Computational scientist @ Argonne National Laboratory
- AI / ML Group @ ALCF
- Working on:
- 🧪 {AI, HPC} for science
- 🚀 training large models on supercomputers
MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization G. Dharuman, K. Hippe, A. Brace, S. Foreman, et al. @ SC’24
Intro to HPC Bootcamp: Engaging New Communities Through Energy Justice Projects
Journal of Computational Science, 2024Thorough Characterization and Analysis of Large Transformer Model Training At-Scale
Proc. ACM Meas. Anal. Comput. Syst. 03/2024MLMC: Machine Learning Monte Carlo for Lattice Gauge Theory
S. Foreman et al. Lattice, 2023 (Proceedings), 12/2023Protein Generation via Genome-scale Language Models with Bio-physical Scoring
@ SC’23, 11/2023DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery […]
@ NeurIPS 2023 AI For Science Workshop, 10/2023Comprehensive Performance Study of LLMs on Novel AI Accelerators
M. Emani, S. Foreman, et al., IPDPS 2024, 10/2023Exploratory Analysis of Climate Data with
ClimRR
S. Foreman, Intro to HPC Bootcamp @ NERSC, 08/2023GenSLMs: Genome-scale language models reveal SARS-Cov-2 evolutionary dynamics
@ SC’22 10/2022Lattice QCD and Particle Physics
A.S. Kronfeld et al., 07/2022Applications of ML to Lattice QFT
D. Boyda, S. Calí, S. Foreman, et al., [arXiv:2202.05838], 02/2022LeapFrogLayers: Trainable Framework for Effective Sampling
S. Foreman, X.Y. Jin, J.C. Osborn, Lattice, 2021HMC with Normalizing Flows [slides]
S. Foreman et al., Lattice, 2021Deep Learning Hamiltonian Monte Carlo [+ poster]
S. Foreman, X.Y. Jin, & J.C. Osborn, @ SimDL Workshop @ ICLR, 2021Machine Learning and Neural Networks for Field Theory
S. Foreman, X.Y. Jin, & J.C. Osborn, SnowMass, 2020Examples of renormalization group transformations for image sets
S. Foreman et al., Physical Review E., 2018RG inspired Machine Learning for lattice field theory
S. Foreman et al., arXiv:1710.02079, 2017Large Energy Density in Three-Plate Nanocapacitors due to Coulomb Blockade
S. Foreman et al., J. Appl. Phys, 2018
References
Convert from HTML to slideshow version of a page by appending /slides
to the end of its URL, e.g.
What | Where | When |
---|---|---|
LLMs on Aurora: Overview | 2025 ALCF INCITE GPU Hackathon | 2025-05-21 |
LLMs on Aurora: Hands-On | 2025 ALCF INCITE GPU Hackathon | 2025-05-07 |
AuroraGPT: Foundation Models for Science | Foundation Models for the Electric Grid | 2025-02-12 |
Parallel Training Methods | Intro to AI-driven Science on Supercomputers | 2024-11-05 |
AuroraGPT: ANL’s General Purpose Scientific LLM | ALCF Hands-on HPC Workshop | 2024-10-30 |
Deep Learning and Foundation Models at Scale | ALCF Hands-on HPC Workshop | 2024-10-29 |
AuroraGPT | HPC User Forum Fall ’24 | 2024-09-04 |
Training LLMs at Scale | ATPESC 2024 | 2024-08-09 |
LLMs on Polaris | SciFM Summer School ’24 | 2024-07-17 |
MLMC: Machine Learning Monte Carlo | Lattice 2023 (Fermilab) | 2023-07-31 |
📆 2025
📆 2024
📆 2023
📆 2022
📆 2021
📆 2020
What | When |
---|---|
🚧 Frameworks Issue with numpy > 2
|
2025-05-03 |
🔥 Building PyTorch from Source on Aurora | 2025-04-28 |
👤 Résumé | 2025-04-26 |
🪛 Torchtune on Aurora | 2025-03-23 |
🚑 Torchtune Patch on Aurora | 2025-03-23 |
🫥 svgbob | 2024-11-15 |
💾 Converting Checkpoints | 2024-10-17 |
🏔️ Spike Skipper | 2024-09-17 |
🍋 ezpz @ ALCF
|
2024-08-23 |
📝 ezpz-v1 | 2024-08-23 |
💅 How to Make Dope Slides | 2024-08-13 |
🎰 Deterministic flash-attn
|
2024-06-17 |
📸 flash-attn on Sunspot
|
2024-06-17 |
🏎️ Megatron-DeepSpeed on Intel XPU | 2024-06-15 |
🐛 mpi4py bug on Sunspot
|
2024-05-25 |
🎲 MCMC + Diffusion Sampling | 2024-04-15 |
🐢 Starting Up Distributed Training on Aurora | 2024-03-21 |
🚂 Loooooooong Sequence Lengths | 2024-02-12 |
🏁 l2hmc Example: 2D U(1)
|
2024-02-12 |
🎢 l2hmc-qcd Example: 2D U(1)
|
2023-12-14 |
🔳 l2hmc-qcd Example: 4D SU(3)
|
2023-12-06 |
🎓 Education
- Ph.D., Physics
- University of Iowa, 2019
- Learning Better Physics: A Machine Learning Approach to Lattice Gauge Theory
- University of Iowa, 2019
- B.S. in Engineering Physics
- University of Illinois at Urbana-Champaign, 2015
- Energy Storage in Quantum Resonators (US Patent #US9741492B2)
- B.S. in Applied Mathematics
- University of Illinois at Urbana-Champaign, 2015
🧑🔬 Professional Experience
- Assistant Computational Scientist
- Argonne National Laboratory, Argonne Leadership Computing Facility (ALCF)
- Lemont, IL | 2022 – Present
- Research lead on scaling large language models (LLMs) and generative AI for science on supercomputers (Aurora, Frontier, LUMI, Leonardo, …).
- Optimize large-scale training of foundation models and language models for scientific applications.
- Collaborate with interdisciplinary teams to enhance simulation efficiency and scalability.
- Focus on AI and HPC for scientific applications, including:
- Developing improved sampling algorithms for lattice quantum chromodynamics (QCD)
- Training large language models on supercomputers
- https://www.alcf.anl.gov/about/people/sam-foreman
- Argonne National Laboratory, Argonne Leadership Computing Facility (ALCF)
- Postdoctoral Researcher
- Argonne National Laboratory, Argonne Leadership Computing Facility (ALCF)
- Lemont, IL | 2019 – 2022
- Applied deep learning to lattice gauge theory and quantum field simulations.
- Developed ML-enhanced Monte Carlo methods for QCD.
- Engaged in AI-for-Science collaborations with national labs and university partners.
- Argonne National Laboratory, Argonne Leadership Computing Facility (ALCF)
- Graduate Researcher
- Argonne National Laboratory, Math and Computer Sciences (MCS)
- Lemont, IL | 2018 – 2019
- Collaborated with ALCF while completing Ph.D., integrating ML into physical sciences workflows.
🏆 Awards and Honors
- ACM Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research, 2022
- Recognized for contributions to the GenSLMs project, which developed genome-scale language models to study SARS-CoV-2 evolutionary dynamics.
- https://www.acm.org/media-center/2022/november/gordon-bell-special-prize-covid-research-2022
- Finalist, ACM Gordon Bell Prize, 2024
- Acknowledged for the MProt-DPO project, which achieved over 4 ExaFLOP sustained performance in multimodal protein design workflows using Direct Preference Optimization.
- https://sc.cels.anl.gov/gordon-bell-argonne-team-breaks-new-ground-in-ai-driven-protein-design/
- DOE Office of Science Graduate Student Research Fellow, 2018
- Awarded by the Department of Energy for outstanding research contributions during graduate studies.
📚 Publications1
- MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows with Direct Preference Optimization
- GenSLMs: Genome-Scale Language Models Reveal SARS-CoV-2 Evolutionary Dynamics
- Applications of Machine Learning to Lattice Quantum Field Theory
- HMC with Normalizing Flows
- Deep Learning Hamiltonian Monte Carlo
- Examples of Renormalization Group Transformations for Image Sets
🎤 Selected Talks2
- AuroraGPT: Foundation Models for Science @ Foundation Models for the Electric Grid [02/2025]
- Parallel Training Methods @ AI-for-Science on Supercomputers [11/2024]
- AuroraGPT @ HPC User Forum, 2024 [09/2024]
- Machine Learning and Foundation Models at Scale @ 2024 ALCF Hands-On HPC Workshop [10/2024]
- Training LLMs at Scale @ ATPESC, 2024 [08/2024]
- LLMs from Scratch @ LLM Tutorial Workshop [02/2024]
- Exascale Science on Aurora @ Intel oneAPI Workshop @ UIC [10/2023]
- Scaling LLMs for Science @ Data-Intensive Computing + AI/ML at Scale [08/2023]
- MLMC: Machine Learning Monte Carlo @ Lattice 2023 [07/2023]
- Generative Modeling and Efficient Sampling @ PASC23 [07/2023]
🎪 Events
Organizer for:
SC24 Workshop: High Performance Python for Science at Scale (HPPSS), November 2024
SC23 Workshop: High Performance Python for Science at Scale (HPPSS), November 2023
Machine Learning and Quantum Computing for Earth Sciences at 17th U. S. National Congress on Computational Mechanics, July 2023
👔 Employment
Position | @ | Start | End |
---|---|---|---|
Assistant Computational Scientist | ALCF | 2022 | – |
Postdoc | ALCF | 2019 | 2022 |
Graduate Researcher | ANL | 2018 | 2019 |
🍎 School
Footnotes
See full list on Google Scholar↩︎
See full list at: samforeman.me/talks↩︎
Citation
@online{foreman2025,
author = {Foreman, Sam},
date = {2025-05-23},
url = {https://samforeman.me/},
langid = {en}
}