Shaswat Senthilkumar
From curious 10th grader to 1st place winner at the Mercer Science & Engineering Fair at Princeton University with groundbreaking ML research on stem cell differentiation
Where Shaswat Started
His Background
- • 10th grade student at West-Windsor Plainsboro HS South
- • Passionate about computational biology and machine learning
- • No prior research or publication experience
- • Interested in applying AI to solve biomedical problems
His Goals
- • Conduct original research in computational biology
- • Win at regional science fairs
- • Learn advanced machine learning techniques
- • Build a strong research profile for college applications
His Vision
"I wanted to use machine learning to predict how stem cells differentiate. If we could understand this process better, we could advance regenerative medicine and help treat diseases."
— Shaswat, before joining YRI
The Research
Working with his YRI mentor, Shaswat developed a machine learning framework to predict stem cell differentiation outcomes using RNA sequencing data—a complex challenge at the intersection of computational biology and AI.
Stem Cell Differentiator: ML-Based Prediction of Stem Cell Differentiation Using RNA-seq Data
Predicting how stem cells will differentiate is crucial for regenerative medicine but extremely complex
RNA sequencing datasets capturing gene expression patterns during differentiation
Machine learning models trained on RNA-seq data to predict differentiation outcomes
Novel approach combining gene expression analysis with predictive ML modeling
ML-Powered Stem Cell Analysis
Shaswat built a sophisticated pipeline that processes RNA-seq data to predict differentiation pathways. His model helps researchers understand which genes are most important in determining cell fate decisions.
The pipeline processes gene expression data to predict stem cell outcomes
Medical Impact
Understanding stem cell differentiation has implications for treating diseases like Parkinson's, diabetes, and heart disease. Shaswat's research contributes to the field of regenerative medicine by providing tools to better predict and control cell fate.
Science Fair Success
Mercer Science & Engineering Fair at Princeton University
The Outcome
1st Place Winner — Mercer Science & Engineering Fair
Computational Biology / Machine Learning
Princeton University
Stem Cell Differentiation Prediction
Advancing regenerative medicine research
YRI helped me turn my interest in computational biology into a real research project. My mentor guided me through the entire process—from understanding RNA-seq data to building ML models. Winning 1st place at Mercer Science Fair was an incredible validation of our work.
10th grader interested in AI and biology, no research experience
1st Place winner at Princeton University science fair with original ML research
Technical Highlights
Gene expression analysis from sequencing data
Machine learning models for differentiation prediction
Understanding cell fate decisions for regenerative medicine
Ready to Start Your Research Journey?
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