Research groups in CLS
The Institution CLS works in several areas where we contribute to future solutions in the areas data science, software construction, distributed and parallel systems, computer architecture, network systems, and network systems security.
Research on fundamental aspects of software technology and computer systems focusing on cloud computing, service computing, model-based computing systems, social networks, time aware systems, data science and applied artificial intelligence (AI), software engineering, networked systems, internetworking and security and privacy.
Data Science: Machine Learning
Research on algorithms and systems for data analysis, machine learning and data mining. We work in healthcare, drug development, climate research, vehicle maintenance and social networking.
GALE: Graph Analytics and Network Learning
Focuses on bridging the gap between Machine Learning and Distributed Systems to address the challenges posed by centralized AI services.
Programming languages and modelling
We investigate programming languages and modelling languages, cyber-physical systems, model based computer systems, compilers and machine leärning.
Software Development with Clouds and Artificial Intelligence
We research Software technology for Cloud computing, and also AI techniques for instance for for health care and smart cities.
Data Systems Lab
We focus on data-driven system design with applications in serverless computing, distributed databases, AI, data stream platforms, graph query systems, and acceleration using emerging new hardware and methods.
Distributed and Parallel Systems
We develop large distributed systems and algorithms in data intelligent cloud services, big data and data analysis systems.
Networked Systems Security
We make networked systems trustworthy by shielding them and their users from attacks and abuse. Our research solving security and privacy problems..
Networked Systems Lab
Networked Systems Lab (NSLab) conducts research and education in the area of design, analysis, and management of next generation networks and services. In particular, our main research focus is making it easy to develop and manage key societal Networked Systems that meet their objectives. Classic examples include: high performance, high reliability, and low-power.
Machine-Intelligence for Networks and Distributed Systems
We develop cutting-edge network systems that combine innovative algorithms, programmability, and AI-based techniques to enable unparalleled efficiency, scalability, security, and automation to modern infrastructures