Most students think publishing research is something that happens in graduate school. These high schoolers proved otherwise.

Below are real examples of research papers published by YRI Fellowship students in peer-reviewed journals and conferences. Each one was completed in 10-12 weeks with PhD mentorship.

Student: Aditya Singla, 11th Grade, Cupertino High School Published: IEEE AAIML 2026 (Tokyo, Japan) Award: Best Oral Presentation

Aditya developed a novel multistep neural network approach to detect anomalies in online operational systems. His model processed over 117,000 features from 39,365 data points, achieving a 2.7x improvement over prior research. He presented his findings at an international IEEE conference in Tokyo and won Best Oral Presentation.

What made it work: A clearly defined problem (cloud system failures), a novel two-step methodology, and strong quantitative results that improved on existing benchmarks.

Student: Ruthwik Dhama, 11th Grade, Enloe High School Published: IEEE Conference

Ruthwik created METHI, an ensemble-based machine learning framework that scores exoplanet habitability. Rather than analyzing one planet at a time, his system can evaluate all known exoplanets simultaneously.

What made it work: An ambitious scope matched with a practical ML approach. The framework had clear real-world applications for astronomical research.

Student: Aarnav Bhat, 11th Grade Published: IEEE ICITSIF 2026

Aarnav used machine learning to identify biomarkers for lung cancer detection, achieving an AUC of 0.983. His model could distinguish cancerous from non-cancerous samples with near-perfect accuracy.

What made it work: Medical relevance, strong statistical results, and a clear contribution to the early detection field.

Student: Trisha Sallakonda, 10th Grade, Emerald High School Presented: ACSEF (3rd Place)

Trisha simulated composting and biogas pathways for urban organic waste, comparing them against landfill baselines. Her models showed that high-participation households could achieve near-complete landfill avoidance.

What made it work: A timely environmental topic, rigorous simulation methodology, and clear policy implications for urban planning.

Student: Avyay G., 9th Grade Award: 1st Place Science Fair, State Qualifier

Avyay integrated air pollution exposure data with genetic susceptibility to predict respiratory disease risk using AI models including survival analysis and SHAP interpretability.

What made it work: Interdisciplinary approach combining environmental data with genetics, plus strong AI methodology for a 9th grader.

Student: Arjun V Doss, 11th Grade, National Academy For Learning (India) Published: Springer Nature Additional: Patent Pending

Arjun developed OxiGen, a photocatalytic system using BiVO4-based nanomaterials to convert CO2 to O2 under visible light. This wasn't just a paper; it was a patentable invention.

What made it work: Novel chemistry, real-world environmental applications, and the combination of publication plus patent filing.

Student: Arya Devanath, 10th Grade, California High School Accepted: Stanford Neuroethics 2026 Award: 3rd Place Science Fair

Arya built ML models analyzing physiological stress responses during rhythmic movement, creating a foundation for virtual dance therapy in addiction treatment. Her Random Forest model achieved an F1 score of 0.857.

What made it work: A unique intersection of personal passion (Bharathanatyam dance) and neuroscience research, with a culturally-grounded therapeutic application.

Student: Ayaan Rustagi, 10th Grade, Rouse High School Published: IEEE Conference Award: 3rd Place Science Fair

Ayaan applied astronomy techniques like pulsar timing to detect Alzheimer's from brain scans, achieving 88.9% accuracy. This cross-domain approach was novel and caught judges' attention.

What made it work: Creative cross-domain thinking that bridged two seemingly unrelated fields.

Looking across all these examples, successful high school research papers share these traits:

• Clear, specific research question — not "I want to study AI" but "Can a multistep neural network detect cloud anomalies better than existing methods?"
• Novel methodology or application — applying an existing technique to a new domain, or combining methods in a new way
• Quantitative results — accuracy scores, AUC values, percentage improvements that reviewers can evaluate
• Real-world relevance — papers that solve actual problems get published faster
• Strong mentorship — every student above worked with a PhD mentor who guided their methodology

These students started with zero research experience. The difference was structured mentorship that gave them a topic, methodology, and writing support from week one.

The YRI Fellowship pairs you with a PhD mentor matched to your interests and guides you through the entire process — from research question to published paper — in 10-12 weeks.