A distributed system is a computing environment in which various components are spread across multiple computers (or other computing devices) on a network. These devices split up the work, coordinating their efforts to complete the job more efficiently than if a single device had been responsible for the task. We are developing and analyzing efficient methods and algorithmic techniques in this field for various tasks.  

High computing power can only be achieved through a combination of powerful computer systems and algorithms that solve the given problem as efficiently as possible. The development of efficient algorithms is a classic branch of computer science. Our research focuses on algorithms for networked systems posing new challenges for the design of efficient algorithms.  

The theory of computation is the branch of computer science that deals with what problems can be solved on a model of computation, using an algorithm, how efficiently they can be solved or to what degree (e.g., approximate solutions versus exact ones).

Swarms of autonomous low cost robots provide an attractive alternative when facing various large-scale tasks in hazardous or hostile environments. Such systems can be made cheaper, more flexible and potentially resilient to faults. Autonomous robots with limited visibility range need to perform local algorithms that use only information of the position the robots and of robots within their limited visibility range. The robots have to perform a common task, e.g. gather at a point, cover agiven area or barrier, or form a given pattern, etc... The goal is to develop and analyze local algorithms for swarm robots for various tasks.