We are a multi-disciplinary research group in computational and data-driven science. Our research interests are particularly oriented towards addressing challenges of scale and complexity. We are active in several areas including Decentralised AI/Federated Learning, Distributed and Cloud Computing, Cybersecurity, Machine Learning and Data-Driven Life Science. We are located at the Division of Scientific Computing, Department of Information Technology, Uppsala University.

Decentralised AI, Federated Learning

We develop methods and software to address decentralised and privacy-preserving AI. We are core contributors to the FEDn open source framework for scalable federated machine learning. Recent projects in the federated setting include federated optimization and semi-supervised learning.

Distributed Systems and Cybersecurity

We address data-centric challenges in distributes systems and cybersecurity. Recent focus areas include scalable and efficient hierarchical storage and information management, image compression, and data-driven vulnerability analysis.

Computation and Data-Intensive Science

We study scientific computing, but with a firm focus on life science application data analysis, utilizing modern computing architectures (including GPU computations and massive parallelism in varying forms). The basic question is "how can we trade experiment result quality for more sophisticated computational methods", giving better results with worse original data.

Learning, Inference and Optimization

The themes of learning, inference and optimization are intimately connected, and power AI and data-driven science. We build the foundations of data-efficient machine learning and optimisation. We also develop methods for performing analysis/inference with scientific data. Non-convex and global optimisation are strong focus areas in our lab.


Andrey Shternshis joins the lab!

We welcome Andrey to the group as a PostDoc, working on fairness and bias-aware design of scientific experiments. Prior to joining Uppsala University, Andrey was a doctoral researcher at Scuola Normale Superiore (SNS), Pisa, Italy. Read more…

Get in Touch

We are always interested in hearing from potential students and collaborators

Find us at:

Division of Scientific Computing,
Department of Information Technology,
Ångströmlaboratoriet, Uppsala University,
Lägerhyddsvägen 1, hus 10 Uppsala

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