Undergraduate-developed open-source library connects student innovation at Khalifa University with the international quantum software community
Khalifa University of Science and Technology announces that quantum-learn, an open-source Python library developed by undergraduate students through the R&D Division of the Khalifa University Quantum Computing Initiative (QCI), has been accepted into the Qiskit Ecosystem.
This achievement brings a student-developed project into an international ecosystem of software built around Qiskit, IBM’s open-source quantum computing platform. It gives quantum-learn greater visibility among researchers, educators and developers worldwide, creating opportunities for the project to reach new users and attract contributions beyond the university.
For QCI, Khalifa University’s official student-led Quantum Computing Club, the milestone demonstrates a pathway from learning the fundamentals of quantum computing to building practical tools for the wider quantum community.
The Qiskit Ecosystem brings together community-maintained packages that integrate with or support Qiskit. Projects applying to join are reviewed against published requirements covering meaningful Qiskit integration, software compatibility, open-source licensing, community standards and active maintenance. Member projects also undergo weekly checks to monitor their continued compliance with the ecosystem’s requirements.
Quantum machine learning (QML) explores how quantum circuits and classical machine learning methods can be combined to tackle more complex machine learning problems.
Developing these models can require users to configure quantum circuits, measurements, optimizers and software specific components before they can begin experiments.
quantum-learn was created to reduce this setup burden by abstracting common lower level configuration and wrapping QML components in higher level, reusable interfaces. Its design introduces estimator style workflows familiar to machine learning practitioners, including methods for fitting models to data and using trained models to generate predictions.
The project also provides backend specific interfaces for PennyLane and Qiskit with a modular structure that can be expanded as the library develops. It is available through PyPI under the MIT open-source licence. Implementation details, examples and guidance are all available through the projects GitHub README and documentation.
The project reflects QCI’s broader ambition: enabling students not only to understand quantum technologies, but to contribute to their development. Guided by the goals of educating, building and connecting, the Initiative combines workshops, hackathons and technical learning with research, collaborative projects, open-source development and engagement with the wider quantum community.
Its R&D Division was established to give students a structured pathway from introductory learning to sustained technical contribution. Student teams work across quantum machine learning, quantum software tooling, quantum error correction (QEC) and quantum chemistry, with quantum-learn serving as the division’s flagship open-source project.
Developing a publicly available library also brings responsibilities beyond writing an algorithm. Students gain experience in software architecture, testing, documentation, version compatibility and collaborative maintenance. These are skills needed to make software understandable and usable beyond its original development team.
The significance of quantum-learn’s inclusion therefore extends beyond a single package. It shows how a student-led initiative can connect education with practical software development, producing work that others can inspect, test and improve.
For Khalifa University, the milestone reflects its commitment to student research and innovation. For QCI, it advances a mission to strengthen the quantum ecosystem through education, research and meaningful open-source collaboration.
quantum-learn remains open to community contributions. Students, researchers, educators and developers at Khalifa University, across the UAE and internationally are invited to test the library and share feedback.
Contributors can also help improve the library’s code, expand its documentation and examples, propose new capabilities and strengthen existing workflows through GitHub pull requests. This collaborative approach creates opportunities for students to work with contributors beyond their institution while allowing future student teams to build on an established project. The ambition is not simply to publish software, but to sustain a tool that can evolve with its users and the wider quantum community.
The project can be explored through its GitHub repository and README, installed through the Python Package Index, and studied through its online documentation. It is now featured on Qiskit’s page for their official third party libraries: Qiskit Ecosystem.
Additional projects and information about QCI’s work are available through the QCI GitHub organization and the Khalifa University Quantum Computing Initiative website.
