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Integrative Scalable Computing Laboratory

A research group at the Department of Information Technology, Uppsala Universtity.

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Usama Zafar joins the lab! Welcome
PhD student in Scientific Computing focusing on Secure Federated Machine Learning Data Science
Open PhD position in Scientific Computing Applied Cloud Computing
Two Open PhD Positions Data Science
FedQAS: Federated machine reading comprehension based on FEDn Data-Intensive Computing

Xiaobo Zhang joins the lab

Posted on May 31, 2021October 17, 2021 By admin No Comments on Xiaobo Zhang joins the lab
Xiaobo Zhang joins the lab

We are happy to welcome Dr Xiaobo Zhang to the lab. Xiaobo will be working in the HASTE project, developing new methods for intelligent management of data streams composed of scientific data objects such as images. He brings expertise on working on compressed data in machine learning and edge computing. Xiaobo Zhao received the M.S….

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HASTE, News

Omar Javed joins the group as a visiting PhD student

Posted on February 15, 2021February 15, 2021 By admin No Comments on Omar Javed joins the group as a visiting PhD student
Omar Javed joins the group as a visiting PhD student

We are happy to welcome Omar Javad for his exchange year as a visiting PhD student! Omar a PhD student in Università della Svizzera italiana (USI), Switzerland. His research interest includes dynamic program analysis, mining software repositories, virtualization and runtime verification. In particular I am investigating dynamic program analysis technique for understanding functional and non-functional…

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Applied Cloud Computing, News

Trusted Execution Environment (TEE) For Federated Learning

Posted on January 14, 2021September 14, 2021 By admin No Comments on Trusted Execution Environment (TEE) For Federated Learning
Trusted Execution Environment (TEE) For Federated Learning

The Scaleout team, in close collaboration with ISCL, was granted SEK 2.1M to explore the use of secure enclaves to increase the veracity in federated learning. Read more about the project here: https://www.scaleoutsystems.com/post/trusted-execution-environment-for-federated-learning

Data-Intensive Computing, FedML, Funding, News

Smart Resource Management for Data Streaming using an Online Bin-packing Strategy

Posted on December 16, 2020September 13, 2021 By admin No Comments on Smart Resource Management for Data Streaming using an Online Bin-packing Strategy
Smart Resource Management for Data Streaming using an Online Bin-packing Strategy

The stream processing framework HarmonicIO is a prototype that addresses the needs for processing streams based on relatively large individual objects. In this regard, it is a specialized streaming framework well-suited for scientific workflows. Salman Toor and Oliver Stein presented this work, and our latest publication  Smart Resource Management for Data Streaming using an Online…

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Applied Cloud Computing, Data-Intensive Computing, HASTE, News, publication, Software

Sadi Alawadi joins the lab as a postdoc focusing on FedML

Posted on September 22, 2020September 22, 2020 By admin No Comments on Sadi Alawadi joins the lab as a postdoc focusing on FedML
Sadi Alawadi joins the lab as a postdoc focusing on FedML

It is great to be able to welcome Sadi Alawadi to the lab! Sadi will work in our project scalable federated machine learning. This postdoc project is part of an eSSENCE initiative is connected to the new cross-disciplinary effort AI4Research at Uppsala University, with the aim to specifically support this effort by research on new e-Science methods…

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FedML, News

Addi Ait-Mlouk joins the lab as postdoc focusing on FedML

Posted on September 22, 2020September 22, 2020 By admin No Comments on Addi Ait-Mlouk joins the lab as postdoc focusing on FedML
Addi Ait-Mlouk joins the lab as postdoc focusing on FedML

It is great to be able to welcome Addi-Ait Mlouk to the lab! Addi will work in our project scalable federated machine learning. This postdoc project is part of an eSSENCE initiative is connected to the new cross-disciplinary effort AI4Research at Uppsala University, with the aim to specifically support this effort by research on new e-Science methods…

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FedML, News

MSc thesis opportunities in privacy-preserving Machine Learning

Posted on November 10, 2019November 10, 2019 By admin
MSc thesis opportunities in privacy-preserving Machine Learning

We have opportunities for a number of MSc thesis students to work with the group in the spring semester 2020. 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…

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Applied Cloud Computing, FedML, News, Open Positions

Challenges

Posted on November 2, 2019November 2, 2019 By admin No Comments on Challenges

The practical problems that arise when going from simple models to big models include: Most simulation algorithms do not scale well to high dimensions. Simulation can becomes prohibitively expensive due to the multiscale nature of systems. Failure of traditional engineering methodology such as sensitivity analysis and optimization due to high dimensionality, non-linearities and stochasticity…. ……

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Uncategorized

Anass and Stefan moves on to new adventures

Posted on September 4, 2019December 14, 2019 By admin No Comments on Anass and Stefan moves on to new adventures

It is with mixed feelings that we say goodbye to Stefan and Annas. Both have contributed with lots of energy and science to the group, but will now move on. Stefan to a role in industry, and Anass to an assistant professorship at Ecole Centrale Casablanca. You will both be missed, and thank you so…

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News, Uncategorized

Highly Scalable Federated Machine Learning

Posted on March 23, 2019August 21, 2020 By admin No Comments on Highly Scalable Federated Machine Learning
Highly Scalable Federated Machine Learning

Artificial intelligence is rapidly transforming our society. Machine learning models will soon be in every digital system we use. For this reason, there is an urgent need for methods and software that allows for development of state-of-the art ML models while protecting the integrity of data owners . In this project we work on algorithms,…

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Data-and simulation-driven life science. Much of our work in eScience and applied ML has applications in life science, and in Systems Biology in particular. We aim to enable data-and simulation-driven scientific discovery.

HASTE - a cloud native framework for intelligent processing of image streams: http://haste.research.it.uu.se/

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Decentralized AI, Federated Learning. One focus area of the group is development of methods and software to address decentralized and privacy-preserving AI. We are core contributors to the FEDn open source framework for scalable federated machine learning:

https://github.com/scaleoutsystems/fedn
Introduction to Federated Learning by Andreas Hellander
Join the discussion on Decentralized AI:

Scaleout Systems is a spin-out from ISCL on a mission to enable decentralized AI and federated learning to production.

https://www.scaleoutsystems.com/

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