⚛️🖥️  Featured Projects

At Pattern Recognition Pty Ltd, we bridge the gap between theoretical innovation and practical application by advancing both geometric and quantum machine learning. Below are two flagship projects that exemplify our expertise and our commitment to hybrid AI systems that work, today.

🌟 Geometric Foundations of Quantum Learning

Project Summary
In this ground-breaking research, we reinterpret Quantum Machine Learning (QML) as a natural extension of Geometric Machine Learning (GML). By treating quantum states as points on curved manifolds, much like covariance matrices or image subspaces, we show how respecting this structure allows for more expressive quantum embeddings.

 Highlights

• Unification of QML and GML using Riemannian and information geometry
  
  

• Applications in diabetic foot ulcer detection and structural health monitoring using hybrid classical–quantum pipelines
  
  

• Detailed mathematical treatment of quantum state geometry
  
  

• Open research directions: Quantum LLMs, quantum RL, and hardware-aware optimization
  
  

Impact
Even with limited qubit counts, our hybrid models demonstrated tangible accuracy gains by combining classical manifold extraction with quantum embedding layers.

Read the full paper on arXiv

🌟 Qubit-Efficient Recommender Systems

Project Summary
How can you build powerful quantum recommender systems without needing 100+ qubits? This project introduces a fully operational Quantum semi-Random Forest (QsRF) architecture that achieves state-of-the-art performance using just 5 qubits.

Highlights

• End-to-end hybrid ML pipeline:
  • SVD + k-means to learn a compressed dictionary
  • QAOA to solve qubit-budgeted feature selection
  • QsRF to generate accurate recommendations
  
  

• Tested on ICM-150/500 datasets, achieving baseline-matching performance
  
  

• Demonstrates real-world quantum usefulness in consumer tech scenarios
  
  

Impact
Our method shows that qubit-efficient architectures are not only feasible, but competitive — opening new doors for near-term quantum deployment.

Read the full paper on ResearchGate

Why It Matters

Together, these projects demonstrate our commitment to:

• Solving real-world problems with hybrid AI tools
  
  

• Making quantum useful today, not just in theory
  
  

• Collaborating across disciplines: medicine, engineering, and consumer applications

Contact us for more information and to get involved