Classiq and UC Chile Launch Quantum Computing Research for Biomedical Imaging
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Insider Brief Classiq and UC Chile have launched a 12-month research project to develop hybrid quantum machine learning algorithms for biomedical image analysis and computational pathology. The project will focus initially on renal pathology applications, including kidney lesion classification, glomerular segmentation, and pattern recognition in histological images. Researchers will use Classiq’s software platform, NVIDIA CUDA-Q, and IonQ quantum hardware to develop and benchmark quantum machine learning approaches against classical methods. PRESS RELEASE — Classiq and Pontificia Universidad Católica de Chile (UC Chile) today announced a joint research project to develop hybrid quantum algorithms for biomedical image analysis, assisted by classical machine learning and the NVIDIA CUDA-Q platform for quantum-classical computing. The 12-month engagement, titled “Enhancing Pathology through Quantum Computing,” is funded through Avanza UC 2025, the Internal Research and Creation Competition of UC Chile. To the collaborators’ knowledge, it is the first announced consortium in Latin America to combine quantum computing, machine learning and computational pathology. The engagement marks quantum computing’s and Classiq’s growing presence in Latin America and reflects the company’s expanding work with academic, research and public-sector institutions, including in health innovation. It also reinforces Chile’s emerging role in quantum computing, AI and advanced technology development. Quantum machine learning applies quantum computing methods to machine learning problems, including classification, pattern recognition and complex data analysis. The initial project focus is on renal pathology, an area of growing public health importance in Chile and across Latin America. This includes applying quantum machine learning to computational pathology, with an initial emphasis on kidney lesion classification, automated glomerular segmentation and semantic pattern search across full histological slides. The work will be conducted in collaboration with Dr. Luciano Rebouças and Dr. Washington Conrado, researchers at Fundação Oswaldo Cruz (FIOCRUZ) and professors/researchers at Universidade Federal da Bahia (UFBA) in Brazil, combining expertise in digital pathology, computer vision and biomedical data analysis using curated histopathology datasets, provided by the Brazilian institutions. The research will leverage the Classiq quantum computing software platform and the NVIDIA CUDA-Q platform to leverage a seamless workflow from algorithm development through to simulation and execution. “Latin America has the scientific talent, institutional momentum and public health needs to support this next stage of quantum computing applications,” said Nir Minerbi, CEO and co-founder of Classiq. “This collaboration brings together quantum software engineering, machine learning and biomedical data expertise in a workflow and project that can help strengthen the regional quantum ecosystem while exploring a practical research path for health.” The project will be led by Dr. Dardo Goyeneche of the Faculty of Physics at Pontificia Universidad Católica de Chile. Dr. Goyeneche is the founder and director of QuDIT, the Quantum Development of Information Theory group at UC, which brings together more than 20 students working on quantum information theory and quantum computing. He also directs Project QuAntü, Chile’s first universal quantum computer initiative, currently under construction since December 2025 at the UC Faculty of Physics.
The team also includes Dr. Daniel Uzcátegui from Universidad Católica de la Santísima Concepción (UCSC), Chile, whose research at the interface between machine learning and quantum information theory provides a key bridge between the two core domains of this collaboration. “This project connects fundamental quantum research with an important biomedical challenge,” said Dr. Goyeneche. “By working with Classiq and collaborators in Chile and Brazil, we are creating a regional platform for quantum machine learning in health, while giving researchers experience with modern quantum software engineering workflows used internationally in research and industry.” The research team will use Classiq’s quantum software platform to model, synthesize and optimize quantum convolutional neural networks, variational quantum classifiers and quantum kernel methods. Selected algorithms will be simulated on NVIDIA AI infrastructure, executed on IonQ quantum hardware, and benchmarked against classical machine learning approaches using standard computer vision metrics. The collaboration aligns with Chile’s National Strategy for Quantum Technologies 2025–2035, a recently launched government initiative aimed at strengthening the country’s quantum ecosystem and expanding national capabilities in advanced computing, secure communications and scientific innovation. The project also supports UC’s efforts to expand quantum computing research and education as part of the Faculty of Physics’ 2025–2029 strategic plan.