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Qu-Alz

Co-built a research system exploring earlier Alzheimer’s risk assessment through brain MRI, machine learning, and quantum methods.

Field
Applied quantum research
Role
Research engineer and co-author
Recognition
SEA Quantathon 1st runner-up · ASEAN IVO Forum presentation
Public repositoryCERN Open Quantum Institute event reportOfficial forum programPresentation archive
Editorial visualization of brain MRI processing feeding classical stage classification and a quantum-derived entropy signal in a research interface.
MRI data moves through image processing, stage classification, and a quantum-derived entropy path before the results are reviewed together.

The project

Qu-Alz began with a research question: could MRI-based stage classification be paired with a quantum-derived signal to support earlier assessment of Alzheimer’s risk?

We investigated that question through a research prototype.

I developed Qu-Alz with Sayed Tahlil Hossain, Dimas Sakti Widyatmaja, and Mutawally Nawwar. We built a working research system that combined medical-image processing, machine learning, quantum computation, and an interface for reviewing the outputs together.

My role

I worked across the research implementation and co-authored the conference paper.

The system connected four pieces:

  • MRI preprocessing and brain-region segmentation with PyTorch models;
  • classification across four stages of cognitive impairment;
  • an Entanglement Entropy Score derived from quantum-encoded image features;
  • a research interface for reviewing the model outputs together.

The quantum path

MRI-derived features were encoded with a ZZFeatureMap, reduced density matrices were computed, and von Neumann entropy produced the Entanglement Entropy Score. The score was then considered alongside the segmentation and stage-classification outputs in the combined research workflow.

From competition work to presented work

We first developed Qu-Alz for SEA Quantathon 2025, where it placed 1st runner-up. We then developed the work into a conference paper, which was accepted for presentation at ASEAN IVO Forum 2025 as “Qu-Alz: Quantum-Enhanced Early Prediction of Alzheimer’s in Southeast Asia.”