Dr. Lauritz Thamsen | University of Glasgow | Systems
I am a Lecturer in Computer Systems in the School of Computing Science at the University of Glasgow. I am generally passionate about making computing more efficient, resilient, and sustainable. To this end, I work on methods and tools that make it easier to create resource-efficient and reliable distributed computing systems, for example through adaptive resource management and carbon-aware computing. A particular focus is on data-intensive applications (e.g. data analytics, scientific workflows, AI/ML) running on cloud or edge infrastructure. At Glasgow, I lead the Carbon-Conscious Computing Lab, I am a member of the Systems Section as well as the Parallelism Group, and I contribute to the Low-Carbon and Sustainable Computing research theme activities. Beyond Glasgow, I co-lead a research collaboration on Adaptive Resource Management with TU Berlin.
Previously, I was a senior researcher in the Distributed and Operating Systems group at TU Berlin, where I drove the research on Adaptive Resource Management with a team of PhD students and lectured on Cloud Computing and Distributed Systems. At the same time, I also collaborated closely with the Operating Systems and Middleware group at Hasso Plattner Institute (HPI), mainly on Distributed Systems Engineering. In addition, I was a guest professor in the Knowledge Management group and the Department of Computer Science at HU Berlin, where I lectured on Data-Intensive Systems and contributed to the research activities of the DFG Collaborative Research Center FONDA.
I got my PhD from TU Berlin, working on dynamic resource allocation for distributed dataflows in the BMBF-funded Berlin Big Data Center and the DFG Research Unit Stratosphere under Odej Kao. Before that, I was part of the Software Architecture Group of Robert Hirschfeld and the Research School at HPI. Furthermore, I have worked at SAP Labs in Palo Alto, California, in the Technology Infrastructure Practice group, under Dan Ingalls, and at Signavio in Berlin.