Integrative Scalable Computing Laboratory

Led by Andreas Hellander and Salman Toor

Modeling & Simulation

We often use stochastic descriptions to model complex systems. Many of our projects involve kinetic Monte Carlo, agent-based models and multiscale modeling. A reoccurring theme is how to leverage distributed e-infrastructure for simulations and how to use machine learning to construct approximations.

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Artificial intelligence

A theme in the group is the use of artificial intelligence and machine learning to make software and infrastructure intelligent, interactive and scalable. We also do disciplinary research into specific areas of ML, such as likelihood-free inference and federated ML.

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Cloud computing & data engineering

Our research on e-Infrastructure and data engineering ranges from development of new ways to manage large and fast data to massively parallel, interactive and cloud native applications, to management and scalability of cloud and edge infrastructure.

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Featured projects

Federated Machine Learning

Federated Machine Learning

Artificial intelligence is rapidly transforming our society. Machine learning models will be in every digital system we use, and it is imperative that we protect the integrity of data owners . In this project we work on training schemes, scalable implementations,...


The group participates in the eSSENCE strategic initiative on eScience, focusing on eScience tools and technologies.

Scaleout Systems

Scaleout Systems is a spin-off from the group, focusing on privacy-preserving AI and cloud-native machine learning.

Follow us on twitter

ABC, Gaussian process emulation, parameterising dynamical Systems, a #julialang package, work with @FeiHeUK and a bunch of very talented students: what’s not to like?

It's two months ahead. We're looking forward to your submission.

* Paper Abstracts Due: Friday, April 3, 2020
* Paper Submissions Due: Friday, April 10, 2020

Our latest work with Stefan Hellander on stochastic chemical kinetics now available online: Quite substantial speedups of high-resolution spatial simulations if I might say so myself 🙂 #hellanderlab #stochss

Federated learning alliances to give rise to models that approximate a centralised global model and better than the best local model alone @A_Hellander @LDN_AI

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