Selva Research Group
Our research focuses on the development of advanced tools to support the systems engineering process, in particular on early design and architecture of complex systems.
Knowledge-Intensive and Interactive Systems Architecture
Every system has an architecture: its essence, a high-level abstraction of its design. System architecture decisions are of critical importance: most of the performance and lifecycle cost of a system are fixed or committed by architectural decisions. And yet, most organizations still select system architectures based on unstructured, 100% human processes. This results in potentially sub-optimal architectures chosen from a very reduced set of candidate architectures. This is because of human limitations: bias, inconsistency, and low "computational speed".
On the other hand, much more structured, computer-aided processes are used in later phases of system design. These tools bring rigor, consistency, and exhaustiveness into the design process. Why can't we use similar processes for system architecture? The answer is that system architecture is a much more open-ended, ill-posed problem that goes well beyond configuration design. This is the kind of task at which humans excel, and computers cannot accomplish.
What is needed is a theory and a set of interactive tools that can combine inputs from both humans and computers to find optimal system architectures. Our group strives to address these problems by using concepts from logical reasoning systems, knowledge engineering, global optimization, and machine learning. We apply these tools to a variety of complex systems, mostly focusing on space systems such as remote sensing and communications satellites. Check out our past and current research projects here.