Cupertino High School junior earns top presentation honor at international AI conference for groundbreaking research on cloud system anomaly detection.

Aditya Singla, a junior at Cupertino High School in California, was awarded Best Oral Presentation at the 2026 International Conference on Advances in Artificial Intelligence and Machine Learning (AAIML), an IEEE conference held at Chuo University's Korakuen Campus in Tokyo, Japan, from March 20 to 22, 2026.

Aditya presented his research paper, "A Novel, Multistep Neural Network Approach to Improve Anomaly Detection in Online Operational Status," which introduces a new methodology for detecting system failures in large-scale cloud infrastructure like IBM's Cloud Console.

The Research

Cloud systems power everything from banking apps to social media platforms. When these systems experience anomalies, unexpected failures or disruptions, millions of users can be affected. Current detection methods often miss critical issues or generate too many false alarms.

Aditya's research addresses this challenge with a novel two-step neural network pipeline that progressively filters suspicious data points to identify true anomalies with greater accuracy.

Key Results

Using real telemetry data from IBM's cloud infrastructure (39,365 data points with over 117,000 features), Aditya's approach achieved:

  • 16 out of 25 ground truth anomalies successfully detected (up from just 6/25 in prior research)
  • Significantly improved true positive to false positive ratio
  • A modular, algorithm-agnostic framework that can be adapted for different detection methods

The idea behind the multistep design is that each network handles one job: the first flags suspicious data points, and the second examines only those flagged points to separate true anomalies from false alarms.

From YRI to International Stage

Aditya developed this research through the YRI Fellowship, working one-on-one with a top-tier PhD mentor matched to his field.

"Presenting at an international IEEE conference in Tokyo was surreal. Winning Best Oral Presentation for my session made the trip even more special. I would like to thank my research mentor, Vamika, for her guidance throughout this journey," Aditya shared after his win.

The research journey took Aditya from learning foundational machine learning concepts to implementing sophisticated neural network architectures and optimization algorithms, skills typically developed in graduate-level coursework.

Why This Matters

Anomaly detection in cloud systems is a critical area of computer science research. Companies like Amazon, Google, Microsoft, and Meta all invest heavily in systems that can automatically detect and respond to service disruptions.

Aditya's contribution, improving detection rates from 24% to 64% while maintaining precision, represents a meaningful advancement that could help engineers identify issues before they impact users.

His paper also introduces several techniques that other researchers can adopt:

  • A feature scoring algorithm to identify the most predictive variables
  • Column and epoch optimization methods for neural network training
  • A suspicion ranking algorithm that enables flexible threshold-based filtering

What's Next

Aditya's paper is now published in IEEE Xplore as part of the AAIML 2026 proceedings, adding a peer-reviewed publication to his portfolio alongside the Best Oral Presentation award, one of the conference's named honors alongside Best Paper, Best Student Paper and Best Poster Presentation. The next edition, AAIML 2027, is scheduled for March 29 to 31, 2027, at Nihon University in Tokyo. If you want to follow the same path, see our guides on how to do AI and ML research in high school and how to publish in IEEE as a high school student.

For high school students interested in AI and machine learning research, Aditya's trajectory demonstrates what's possible: from no prior research experience to international recognition, with the right mentorship and a structured approach.

The YRI Fellowship pairs high school students with PhD-level mentors to conduct original research, publish papers, and compete at top science fairs and conferences. Learn more about the program or apply today.

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