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 initially focus on renal pathology applications such as classification of renal lesions, 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 the Pontifical University of Chile (UC Chile) today announced a joint research project to develop hybrid quantum algorithms for biomedical image analysis, leveraging the NVIDIA CUDA-Q platform for classical machine learning and quantum classical computing.
The 12-month initiative, titled “Enhancing Pathology with Quantum Computing,” is funded through Avanza UC 2025, UC Chile’s internal research and creative competition. To the best of the collaborators’ knowledge, this is the first consortium announced in Latin America that combines quantum computing, machine learning, and computational pathology.
The partnership marks Classiq’s growing presence in Latin America with quantum computing and reflects the company’s expanding work with academic, research and public sector institutions, including health innovation. It also strengthens Chile’s new role in quantum computing, AI and advanced technology development.
Quantum machine learning applies quantum computing techniques to machine learning problems such as classification, pattern recognition, and complex data analysis. The project’s initial focus will be on renal pathology, an area of increasing public health importance in Chile and throughout Latin America. This includes applying quantum machine learning to computational pathology, with an initial focus on renal lesion classification, automatic glomerular segmentation, and semantic pattern search across complete histological slides.
The study is carried out in collaboration with Oswaldo Cruz Foundation (FIOCRUZ) researchers Dr. Luciano Rebouzas and Dr. Washington Conrado, professor/researcher at the Federal University of Bahia (UFBA) in Brazil, and combines expertise in digital pathology, computer vision, and biomedical data analysis using selected histopathology datasets provided by Brazilian institutions. This research leverages the Classiq quantum computing software platform and the NVIDIA CUDA-Q platform to take advantage of a seamless workflow from algorithm development to simulation to execution.
“Latin America has the scientific talent, institutional momentum, and public health needs to support the next phase of quantum computing applications,” said Nil Minervi, CEO and co-founder of Classiq. “This collaboration will integrate expertise in quantum software engineering, machine learning, and biomedical data into workflows and projects that will help strengthen the region’s quantum ecosystem while exploring practical research avenues for health.”
The project will be led by Dr. Dardo Goineche from the Department of Physics at Universidad Católica de Chile. Dr. Goyneche is the founder and director of QuDIT, the University of California’s Quantum Development Information Theory Group, which brings together more than 20 students working on quantum information theory and quantum computing. He is also leading Project Quantü, Chile’s first universal quantum computer initiative, currently under construction at the University of California Department of Physics starting December 2025. The team also includes Dr. Daniel Uzcategui from Universidad Católica Santissima Concepción (UCSC) in Chile, whose work at the interface of machine learning and quantum information theory is an important bridge between the two core areas of this collaboration.
“This project combines fundamental quantum research with important biomedical challenges,” said Dr. Goyneche. “By working with Classiq and our collaborators in Chile and Brazil, we are building a regional platform for quantum machine learning in health, providing researchers with experience in 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 are simulated on NVIDIA AI infrastructure, run on IonQ quantum hardware, and benchmarked against classical machine learning approaches using standard computer vision metrics.
This cooperation is in line with Chile’s National Strategy for Quantum Technologies 2025-2035. This is 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 will also support UC’s efforts to expand research and education in quantum computing as part of the Department of Physics’ 2025-2029 Strategic Plan.
