NSF HDR Machine Learning Challenge

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Accelerated AI Algorithms for Data-Driven Discovery logo

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Theme: The HDR ML Challenge program is hosting its second FAIR challenge for 2025, presenting three scientific benchmarks for modeling out of distribution in three critical areas: Neural Forecasting, Climate Prediction using Ecological Data, and Coastal Flooding Prediction over time. Machine learning problems are often driven by the quality of the available training datasets. Models are very effective at interpolating across their training datasets to find patterns and trends. In this challenge, we ask models to extend beyond their training by performing out of domain extrapolation to practical critical scientific process that have not yet been well studied. As with the first challenge, we will host three distinct sub-challenges on different scientific problems.

Learn More About the Three Challenges:

What’s Happening Now?


Hackathons, Datathons, and more!


University of Maryland, Baltimore County – DATATHON (In progress)

December 1 to 15, 2025

University of Colorado, Boulder – HACKATHON

December 12, 2025

NSF HDR Institutes – (VIRTUAL) HACKATHON

December 18, 2025

Sign up to participate


Upcoming Workshops!


FAIR in ML, AI Readiness, & Reproducibility (FARR) Workshop 2026

Join us in Washington, D.C., at the AGU Conference Center for the ML Challenge Awards Ceremony

April 8-9, 2026

Year 2: Sponsoring Partners

National Science Foundation logo

Amazon Web Services logo
AMD logo
NVIDIA logo
Lambda logo
Codabench logo

Get Involved:

Become a Sponsor!

Organize a Hackathon!

Come and Join as a Participant!

Our Year 2 Challenge is Available through January 31st, 2026

Theme:  A collaborative effort among three of the five NSF HDR institutes. Each HDR institute presented an ‘Anomaly Detection‘ problem to answer questions using complex datasets in polar science, astrophysics, ecology, and evolution. This challenge was geared towards bringing awareness to the broader community about the complexity of using deep learning for this problem since the availability of well-labeled datasets or training through systematic procedures, such as masking, is often insufficient.

Learn More About The Three Challenges:

Sea Level Rise Scenario Tool Map

Highlights


Kick-off Hackathon Events

Approximately 10 local hackathon events to kick-off the 1st ML challenge were organized at several institutions such as University of Maryland, Baltimore County, University of Washington, and the University of California, San Diego.

AAAI 2025 Workshop and Challenge on Anomaly Detection in Scientific Domains

The workshop was co-located with The 39th Annual AAAI Conference on Artificial Intelligence.

AAAI, 2025 Workshop Attendees
Special Recognition of ML Challenge Winners

Scholarship

NSF HDR Machine Learning Challenge (A FAIR Perspective)

Dr. Philip Harris (Director, A3D3), Massachusetts Institute of Technology (HDR Ecosystem)

FAIR in ML, AI Readiness, & Reproducibility (FARR) Workshop,

AGU Conference Center in Washington D.C. (October 9 – 10, 2024)

Invited Talk at a ML Commons virtual event held in February 2025.

K-12 Connection

Hack The Nest 2025

iHARP’s Challenge: “Machine Learning to Predict Anomalous Flooding Events.”

iHARP Focused Outcomes: Proof-of-concept App; Virtual High School Hackathon Showcase

Institutional Organizers


The ML challenge was led by faculty, post-doctoral, and student researchers within the HDR community from the several academic institutions:

UMBC logo

MIT Logo

Ohio State University logo

University of Colorado Boulder logo

University of Washington Logo

Duke University logo

University of Minnesota logo

University of Illinois logo

Princeton University

Year 1: Sponsoring Partners


National Science Foundation logo

Amazon Web Services logo

Codabench logo

NERSC logo