All Projects
Complete portfolio of research and development projects
ProcTwin (2025-2029)
Integrated modelling for sustainable and optimized steel manufacturing processes. ProcTwin develops a demonstration platform to predict and visualize best use of multiple processing steps in a steel manufacturing chain using intelligent coupling of interconnected processing steps through numerical simulation, soft sensors, and distributed machine learning.
FEDn - Scalable Federated ML (2020-2022)
FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning (FedML) developed by researchers from Uppsala university and Scaleout Systems. FEDn enables highly scalable cross-silo and cross-device use-cases over FEDn networks, motivated by the need for AI on private data and facilitating collaborative machine learning.
Privacy-aware Federated Database Infrastructure (2018-2020)
Building an infrastructure of federated database integrating major research data sources for privacy-preserving register data analysis in Sweden. The project developed a privacy-aware federated database while advancing data federation and privacy-preserving techniques to create a scalable, practical infrastructure and research testbed.
Knowledge Discovery in Databases (KDD) (2014-2018)
Data Mining and Knowledge Discovery in Databases/Big Data. In this project, we focused on extracting association rules by developing new algorithms and approaches applied to transportation data. An association rule represents a conditional relationship between sets of items within large datasets.