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Resources and Tips for Machine Learning Researchers at Princeton

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Training/Workshop Programming Languages Research & Data Analysis

Thu, Sep 24, 2026

4:30 PM – 5:30 PM EDT (GMT-4)

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Details

This information session aims to provide an overview of the machine learning (ML) resources at Princeton with an emphasis on the Research Computing systems. The following topics will be discussed:

Overview of the Research Computing Systems for ML
- GPU nodes on Adroit, Della, Stellar/Stellar-AI, Tiger and Citadel
- New Grace-Hopper GPU nodes
- MIG GPUs on Della
- Understanding job priority
- Multi-GPU training with PyTorch
- Tips for using Hugging Face
- Large ML datasets that are already available (e.g., ImageNet)
- Cryo-EM nodes

Overview of the A.I. Lab and PLI GPU Nodes
- Node specifications
- Who has access?
- OpenAI API
- New H200 GPUs on the way
- Social hour and seminars

Other Hardware Resources
- Some departments have their own GPU nodes

Data and Intelligent Systems (DaIS)
- Faculty seminars
- Classes
- Graduate certificate program
- Minor program

Easy to use LLMs
- A.I. Sandbox for secure API access to LLMs
- Web app for using LLMs by DDSS (Blackfish)
- Local inference API for Open LLMs on Research Computing systems
- University-supplied AI tools

ML in the Cloud
- Learn about obtaining free cloud credits (AWS, GCP, Azure)

Training Workshops and Classes
- Learn about educational resources

See the full Research Computing training schedule or subscribe to the Research Computing mailing list.

Speakers

Hubert Strauss's profile photo

Hubert Strauss

Hubert is a Research Software Engineer II in Princeton Language and Intelligence.

Lawrence Ng's profile photo

Lawrence Ng

Lawrence Ng is a Research Software Engineer at the Princeton AI Lab.

Anushka Acharya's profile photo

Anushka Acharya

Associate Research Engineer, Research Computing

Princeton University

Background: Bachelor of Science in Computer Science and minor in Mathematics 



Prior to joining the RSE group at Princeton, Anushka worked in the Digital Humanities Lab at Ramapo College as a Software Developer Intern.  There, Anushka developed a web centric ETL tool and applied Machine Learning models to analyze an expansive archive of historical documents. She also worked as a Software Engineer intern at Memorial Sloan Kettering Cancer Center, where she developed and implemented different workflows to automate Hospital Management System processes.


Jonathan Halverson's profile photo

Jonathan Halverson

Research Software and Computing Training Lead

Princeton University

Jonathan Halverson is the Research Software and Computing Training Lead with Research Computing.

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