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Summer School 2024


WELCOME TO THE SciFM SUMMER SCHOOL

MICDE recently organized the SciFM conference and had an incredible reception for the event. Based on the feedback from that meeting and further discussions with National Lab and academic partners, we are excited to organize the SciFM Summer School from July 8 to July 26. We wish for this to be a recurring event hosted at different locations across the country. The first instance is going to be run in parallel at the University of Michigan (UM) and at Argonne National Laboratory (ANL). The summer school will:

  • Develop technical plans for specific instances of SciFMs;
  • Involve a hackathon to jumpstart the construction of SciFMs;
  • Act as an incubator for ideas;
  • Serve as a training ground for researchers and students;
  • Further a vision for a national SciFM ecosystem.

Apply to Participate!

Fill in the google form below or access it here.

Core Organizers

Venkat Viswanathan
Venkat Viswanathan
Associate Professor of Aerospace & Mechanical Engineering
University of Michigan
Karthik Duraisamy
Karthik Duraisamy
Director of MICDE
University of Michigan
Arvind Ramanathan
Arvind Ramanathan
Computational Science Leader 1
Argonne National Laboratory

Hackathon Organizers

Anima Anandkumar
Anima Anandkumar
Bren Professor of Computing and Mathematical Sciences
California Institute of Technology
Michael Mahoney
Michael Mahoney
Group Lead Machine Learning and Analytics
Lawrence Berkeley National Laboratory
Los Alamos National Laboratory
Los Alamos National Laboratory
  • Date
    Agenda
  • July 8

    1. Welcome and Summer School Goals

    2. Successes of SciFM

    3. FoundSci DARPA program

  • July 9

    1. FoundSci DARPA program

    2. Vision for SciFM Institute

  • July 10

    1. 09:30

       - 

      Tutorial 1a - Data Modalities

    2. 01:30

       - 

      Tutorial 1b - Tokenization

  • July 11

    1. 09:30

       - 

      Tutorial 2a - Training Models

    2. 01:30

       - 

      Tutorial 2b - Diffusion Models

    3. 03:00

       - 

      Tutorial 2c - Scaling Laws

  • July 12

    1. 09:30

       - 

      Tutorial 3a - Retrieval-Augmented Generation (RAG)

    2. 01:30

       - 

      Tutorial 3b - Agents for Biology

    3. 03:00

       - 

      Tutorial 3c - Agents for Chemistry

  • July 15

    1. Goal Setting for Hackathon

  • July 16

    1. Hackathon

  • July 17

    1. Tutorial 4 - AI Accelerators - GPUs and Specialized Hardware

  • July 18

    1. Tutorial 5 - Federated Learning

  • Week 3

    1. Hackathon

  • July 25

    1. Hackathon Team Presentations

  • July 26

    1. Keynote - Open questions for Foundation Models for Science

    2. Panel - Security, Equity, Safety

    3. Ecosystem Gathering (Academia, National Labs, Venture Funding, Philanthropy)

    4. Future Outlook

Participants will explore innovative applications of Foundation Model in four application domains:

  1. Materials -

    Foundation Models for material science have been used for a range of material property prediction, retrosysnthesis and structure search tasks.

  2. Biology -

    In Biology, Foundation Models have enable numerous breakthroughs including protein structure prediction and the classfication of emergent variants of viruses.

  3. Computational Science -

    A Computational Science Foundation Model capable of designing and orchestrating computational research campaigns will enable scientists to focus on domain science through the creative specification of hypotheses and greatly accelerate scientific discovery.

  4. Partial Differential Equations -

    Foundation Models may be the route to enabling data efficient, general purpose PDE solvers.