Ayaan Rustagi
Applied astrobiology techniques to detect Alzheimer's from brain scans, achieving 88.9% accuracy
Where Ayaan Started
His Background
- • 10th grader at Rouse High School in Georgetown, TX
- • Interested in AI and its applications in healthcare
- • Fascinated by the intersection of space science and biology
- • No prior research or publication experience
His Goals
- • Use AI to detect motor neuron disease patterns
- • Publish original research in a peer-reviewed venue
- • Compete at science fairs with innovative cross-domain research
- • Bridge multiple scientific disciplines in a single project
The Problem He Wanted to Solve
"I'm interested in using AI to detect motor neuron disease. I wanted to find a way to apply techniques from completely different fields, like astronomy, to solve problems in neuroscience that traditional approaches were missing."
— Ayaan, before joining YRI
The Research
Working with his YRI mentor, Ayaan developed a novel cross-domain approach that applies astrobiology-inspired signal processing techniques to brain disease pattern recognition. By adapting methods used to analyze pulsar timing data in astronomy, he created AI models capable of detecting Alzheimer's patterns in brain scans with remarkable accuracy.
Astrobiology-Inspired AI Models for Brain Disease Pattern Recognition
Early detection of neurodegenerative diseases remains challenging with conventional methods
Applied pulsar timing techniques from astronomy to analyze brain scan patterns
Cross-domain AI models adapting astrobiology signal processing for neuroimaging
88.9% accuracy in detecting Alzheimer's patterns from brain scans
Cross-Domain Signal Processing
Ayaan's breakthrough insight was recognizing that signal processing techniques used to detect faint pulsar signals in noisy astronomical data could be adapted to identify subtle disease patterns in brain scans. This cross-pollination of methods between astrobiology and neuroscience represents a genuinely novel research direction.
Pulsar timing and signal detection techniques adapted for biomedical use
Machine learning models trained on cross-domain features
High-accuracy Alzheimer's detection from brain scan analysis
The Outcome
IEEE Published + 3rd Place Science Fair
IEEE Conference Paper
3rd Place Award
AI, Neuroscience, Astrobiology
IEEE
Ayaan with his 3rd place science fair award
I applied astronomy techniques like pulsar timing to detect Alzheimer's from brain scans, achieving 88.9% accuracy. YRI helped me bridge astrobiology and neuroscience, and I won 3rd place at my science fair.
10th grader interested in AI and healthcare, no research experience, no publications
IEEE-published author, 3rd place science fair winner with cross-domain AI research
Why This Research Matters
Accuracy in detecting Alzheimer's patterns using astrobiology-inspired methods
People living with dementia worldwide who could benefit from earlier detection
First application of astrobiology signal processing to neurodegenerative disease detection
Ready to Start Your Research Journey?
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