Data-Intensive Computing

PhD student in Scientific Computing focusing on Secure Federated Machine Learning

May 11, 2022May 11, 2022 Salman Toor No Comments

Project Description Artificial intelligence (AI) is at the core of modern-day applications. With the advent of massive datasets, the last two decades were dedicated to improve the mathematical modeling and training processes; And recently the focus has shifted towards security, privacy and trust based AI assisted solutions. Together with a number of other viable solutions,…

Data Science, Data-Intensive Computing, Federated Learning, FedML, News, Open Positions

Open PhD position in Scientific Computing

May 3, 2022May 3, 2022 Salman Toor No Comments

We have one open PhD position focusing on Cybersecurity and Machine Learning for Critical Infrastructures Application submission deadline: May 16, 2022 The application submission link is available on the following page: https://www.uu.se/en/about-uu/join-us/details/?positionId=501061 This PhD position is part of the eSSENCE – SciLifeLab graduate school in data-intensive science. The school addresses the challenge of data-intensive science both from…

Applied Cloud Computing, Data Science, Data-Intensive Computing, News, Open Positions

FedQAS: Federated machine reading comprehension based on FEDn

February 14, 2022February 14, 2022 admin No Comments

Machine reading comprehension (MRC) of text data is a complex NLP problem with a lot of ongoing research fueled by the release of the Stanford Question Answering Dataset (SQuAD). It is considered to be an effort to teach computers how to “understand” a text, and then to be able to answer questions about it using…

Data-Intensive Computing, Federated Learning, News, publication, Software

Proactive Autoscaling for Edge Computing Systems with Kubernetes

December 21, 2021December 21, 2021 Salman Toor No Comments

Happy to announce our newly accepted article: Accepted at the 14th IEEE/ACM International Conference on Utility and Cloud Computing UCC 2021. Abstract With the emergence of the Internet of Things and 5G technologies, the edge computing paradigm is playing increasingly important roles with better availability, latency-control and performance. However, existing autoscaling tools for edge computing…

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

Trusted Execution Environment (TEE) For Federated Learning

January 14, 2021September 14, 2021 admin No Comments

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

December 16, 2020September 13, 2021 admin No Comments

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…

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

“Ten simple rules” for establishing a national scale OpenStack cloud e-infrastructure for science

December 2, 2017December 2, 2017 admin No Comments

The SNIC Science Cloud (SSC) team has published a paper in the 2017 conference on IEEE eScience. SNIC Science cloud has been an infrastructure project run by the Swedish National Infrastructure for Computing (SNIC) with the purpose to assess if and how SNIC should offer cloud infrastructure to the scientific community. The project is now coming…

Applied Cloud Computing, Data Science, Data-Intensive Computing, News, OpenStack

Hierarchical Analysis of Spatial and Temporal Data

May 30, 2017February 6, 2019 admin No Comments

The HASTE project, a SSF-funded project on computational science and big data, takes a holistic approach to new, intelligent ways of processing and managing very large amounts of microscopy images to leverage the imminent explosion of image data from modern experimental setups in the biosciences. One central idea is to represent datasets as intelligently formed…

Data Science, Data-Intensive Computing, ReserachSlider

Postdoc in Scientific Computing/Applied Cloud Computing

July 1, 2016July 1, 2016 admin No Comments

We are looking for a talented individual to join our efforts on creating smart and scalable cloud services to support simulation-driven scientific discovery via large-scale computational experiments such as parameter sweeps. This is a classic and very important problem that we will approach in new ways, leveraging recent advances in cloud computing, data-intensive computing and machine…

Applied Cloud Computing, Data Science, Data-Intensive Computing, News, Open Positions

Fredrik Wrede joins the group

May 13, 2016May 13, 2016 admin No Comments

We are very happy to welcome Fredrik Wrede, MSc. in Bioinformatics, to the group. Fredrik was accepted as a PhD student in CIM, the Center for Interdisciplinary Mathematics. His project will center around intelligent cloud services for processing and making sense of massive amounts of data, for example generated by large computational experiments in systems…

Applied Cloud Computing, Data-Intensive Computing, News, StochSS