Professor Dr. Jussi Rintanen
Department of Computer Science (AISS)
An internationally leading researcher in Artificial Intelligence,
especially in model-based methods for advanced decision-making and reasoning as well as intelligent software systems,
with over two decades of experience in both fundamental and
applicative research in Computer Science.
A main strand in Rintanen's research has been in automated reasoning,
constraint programming and combinatorial search, and their applications
in constructing intelligent software systems that are impossible
to construct by using conventional software engineering technologies.
Prof. Rintanen obtained his PhD degree in Computer Science from the Helsinki University of Technology in 1997, held research and teaching positions at the universities of Ulm and Freiburg between 1997 and 2005, and worked in Australia from January 2006 until September 2012, including as a Principal Researcher at National ICT Australia in various roles as a deputy program leader, project leader of multiple projects, and the leader of the Planning and Diagnosis group, and as an Adjunct Associate Professor at the Australian National University (Canberra) and at Griffith University (Brisbane). Further details in CV.
Prof. Rintanen's research has been applied to
discrete and hybrid systems control (planning), monitoring, and diagnosis,
as well as the Smart Grid (intelligent electricity networks)
and the construction and management of complex large-scale software systems.
A main objective of the research has been to understand, automatically, what happens in a complex system (monitoring, diagnosis, state estimation), what could happen (contingency analysis), and how to control the system according to given cost and safety objectives and to respond to faults and other exceptional and unpredictable situations.
More recently, Prof. Rintanen's research has addressed the construction of complex large-scale software systems in knowledge-intensive domains: software is synthesized automatically from formal high-level specifications. This leads to immense cost and time savings in comparison to conventional software engineering, increases the quality, flexibility and modifiability of software, reduces the testing and validation effort, as well as enables more exhaustive and thorough automated validation methods. A longer term objective in the research is the deeper and deeper embedding of intelligence in all manner of software systems, as well as the design and management of organizational processes by automated means.