The first cohort

Ninth grade, no research experience, ISEF Grand Award

Bradley entered ninth grade in summer 2024 with a strong foundation in math, physics and Python from Ardent, and no research experience at all. He joined a three-student pilot cohort for Ardent AI Scientist.

Year one

Detecting exoplanets in NASA light-curve data

He compared AI models and found that a simple decision tree achieved over 99% accuracy, whereas the neural network performed poorly on small datasets.

His first research project qualified for ISEF.

Read the project →

Year two

Grading and forecasting coral reef bleaching

He developed a neural network that grades bleaching severity from reef imagery and several AI models that forecast bleaching up to 12 weeks in advance.

It won a Grand Award at ISEF 2026.

Read the project →

This project would be credible as an undergraduate capstone or early-stage graduate contribution.
Judge, Buckeye Science & Engineering Fair

What your student actually does

Chooses their own question. Not a canned assignment, in a field they want to investigate.
Works with real scientific data. Medical images, genomic data, environmental sensors, satellite observations, all published by researchers worldwide.
Uses the models the field uses. They select the models, run the experiments, compare results, and find out what the evidence will and will not support.
Finishes with a complete project. Paper, abstract, figures, science-fair poster, and the preparation to explain all of it to a judge.
No AI experience required. Students learn the concepts, tools, and methods when the research creates a reason to learn them.

Ardent AI Scientist

Ninth grade, no research experience, ISEF Grand Award

Detecting exoplanets in NASA light-curve data

Grading and forecasting coral reef bleaching

What your student actually does

See it before you apply

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