The Corpore Sano group at the Computer Science department of UiT conducts basic systems research investigating, for instance, distributed run-times for federated cloud computing. Scalability, performance, ease-of use, privacy, security and fault-tolerance are fundamental properties being targeted. We are developing proof-of concept, proof-of performance and proof-of applicability prototypes in an experimental systems context. Particularly, deployable proof-of applicability prototypes are important for collaboration with our inter-disciplinary research partners.
Professor Dag Johansen, group leader
Johansen is particularly focusing on distributed systems architectures and their implementations. This includes run-times for federated IoT/mobile/cloud computing, run-times for data management, fault-tolerance, security, and privacy, small data analytics systems, disruptive sport technologies, and medical intervention technologies.
Associate professor Håvard D. Johansen
Johansen is concerned with the privacy and security of distributed systems. His work includes epidemic protocols for software patches, large-scale monitoring of athletes using mobile devices, and trusted computing using novel hardware architectures.
Since 2015, he is also the ACM SIGOPS Information Director.
Assistant professor Robert Pettersen
In between teaching introductory computer science, Pettersen has worked with trusted computing using novel hardware architectures and secure edge computing. His PhD work was in alleviating latency issues in mobile/cloud applications. His current research interest is in sensor-based motion tracking of athletes in sports requiring precise technique.
Postdoc Lars Brenna
Brenna has worked in push-based distributed systems in general and with high-performance stream processing specifically. He is currently interested in the intersection of computer science and nutritional science, working on collection and analysis of nutritional data from athletes.
Gjerdrum’s research specializes in distributed systems, operating systems and analytics. His current efforts utilize commodity trusted computing infrastructure to implement a trusted data processing and inference runtime enabling applications to host and process privacy sensitive data on potentially untrusted third-party could platforms.
Prior to pursuing his PHD, Gjerdrum was employed by The Applications and Services Group (ASG) within Microsoft, working on document processing, information retrieval and analytics for the Office 365 cloud platform.
His research interests are in distributed systems, data analytics and privacy preserving technologies. He holds a MS in Distributed Software Systems (2017) from the Department of Computer Science at Technische Universität Darmstadt (TU Darmstadt), Germany. Prior to his Master’s degree, he worked in different roles at Media Lab Asia, IBM Software Labs and Persistent Systems Ltd.
His research interests include distributed systems, operating systems principles, storage, privacy and security. He is currently investigating ways to enforce security policies (e.g. GDPR) associated with data, in a way that is transparent to users and application developers.
Kim Hartvedt Andreassen: “Pub/Sub Video: Systems Practice and Experiences” (Capstone project)
Christoffer Hansen: “Delegation of Access Rights in Decentralized Athlete Quantification Systems” (Capstone project)
Helge Hoff: Implementing a subset of the GDPR (Capstone project)
Jon Foss Mikalsen: “Scaling Blockchains with Byzantine Consensus” (Capstone project)
Tor-Arne Schmidt Nordmo: “Using Machine Learning in Edge Analytics” (Capstone project)
Enrico Tedeschi: “Trading Network Performance for Cash in the Bitcoin Blockchain” (Masters thesis)