The Artificial Intelligence Group conducts interdisciplinary research to develop and combine methods and techniques from classical Artificial Intelligence and Soft Computing to solve real world problems. In the group’s view, handling uncertainty and imprecision is a quest not only because they are inherent in many problems, but also because tolerating them helps to obtain tractable solutions. With a belief that a good system needs a solid foundation, research work is carried out for both theories and applications.
Currently, research activities in the group are focused on natural language processing and uncertain and imprecise knowledge representation and reasoning, for applications in various domains such as text processing and the World Wide Web.

The DSS, a kind of information systems, is rapidly becoming an integral component of management work. The DSS is expected to serve the decision maker by extending his or her capacity to process the mountain of information encountered during the course of making a decision. Nowadays, DSS should be based on the two new information technologies: data warehousing and data mining. The data warehouse contains data that are primarily oriented to decision making, and data mining techniques can help to discover useful knowledge from the data warehouse.
The main activities in the group focus on three important aspects: (1) investigating relevant techniques in DSS and data mining. (2) studying available tools in data warehousing and data mining (3) developing real life applications using DSS, data warehousing and data mining technologies.

Embedded systems are devices that include programmable processors but are not themselves intended to be general-purpose computers. Examples of embedded systems are printers, modems, PDA (Personal Digital Assistant), robot manipulators, etc. Complex embedded systems such as robotic systems interact with the physical world, and consist of possibly distributed sensors, actuators, and processors.
The group’s research focuses on modeling, design, and simulation of complex systems, i.e., systems that mix different kinds of operations such as signal processing, feedback control, and user interface. Issues such as identifying and defining concurrent models of computation as well as geometrical and physical constraints needed for physics-based simulation are investigated. Research work also includes implementation of embedded systems based on approaches such as hardware/software co-design or component-based design.

Since 1980s, the creation of the microprocessor has been revolutionizing instrument design. Thanks to it, not only tracseional instruments have become “smart”, but also entirely new kinds of instruments have emerged. With their extensive computing capability contained in a small integrated circuit (IC) microprocessors have invaded the mind of design engineers. As the size and complexity of digital systems increase, more computer aided design (CAD) tools have been introduced into the hardware design process. The newest adcseion to this design methodology is the hardware description language (HDL). Based on HDLs, new digital system CAD tools have been developed and are now being utilized by hardware designers. System-on-a-chip (SoC) design is defined as designing a complex IC that integrates the major functional elements of a complete end product into a single chip or chipset.
Almost research activities in the group focus on applications in industrial, medical, chemical and telecommunication areas. These applications are either based on microprocessor systems or related to SoC design.

Parallel Processing and Network Computing Parallel processing becomes a key technology of the 21st century for not only scientific research, but also for commercial/industrial applications. The problem of increasing demands of computational power can be solved only by using parallel and distributed architectures like multiprocessor systems and networks of computer systems.
The principal research activities in the group focus on two important aspects, namely: (1) parallel programming environment/tools; (2) parallel algorithms and applications in science and engineering. In the first aspect, the objectives of research work are to provide tools that can help users to easily and effectively develop their parallel applications on the network-based parallel architectures such as SMP, clusters and networks of workstations. Tools are provided at various levels, including program design tools, monitoring, debugging tools and also performance evaluation tools. Tools can be fairly evaluated only when they have users, and hence the research group has collaborated with other research partners to develop parallel algorithms and also methodologies that can be used in scientific computing applications such as modeling and simulations.