The analysis and design of a system of dynamical systems that perceive, reason, learn and act intelligently is the thrust area of research in the PES Centre for Intelligent Systems. The interconnection of simple dynamical systems can lead to seemingly inexplicable complex overall behaviour with the causes and effects not obviously related. Aristotle summed up well: β€œThe whole is greater than the sum of its parts.”

All systems that surround us today – economical, political, ecological or social – consist of diverse, interconnected and interdependent entities which adapt to their environments. The overall behaviour of such systems is often unpredictable as a system of systems is inherently complex, nonlinear and time-varying. Complex systems are about indirect effects. The objective here is the development of tools for the analysis and design of such complex systems.

Cooperative systems are a class of system of dynamical systems with each system being autonomous. The latter balances self-directedness and self-sufficiency with the ability to handle dynamically changing environments. The possibility of integrating human and machine abilities is well within the scope of this research. The focus is to develop and implement such autonomous systems, and the networking of such systems. This includes embedded computational architectures, and dependable and reconfigurable computing.

Decision support systems for healthcare are another class of system of dynamical systems, and telemedicine a logic conclusion. An integral part of this would be interdisciplinary innovation in the design and development of intelligent medical instruments capable of non-invasive measurements and processing data towards intelligent reactions. This includes the development of intelligent algorithms for the analysis of bio-signals, medical image pro-cessing, bio-sta-tis-tics, health infor-mation systems, clinical support systems, medical tele-commu-nica-tion and net-working intelligent systems using both symbolic AI and compu-tational intelli-gence.


  • To understand the behaviour of complex systems, and to design controllers for such systems.
  • Using a systems approach to arrive at computationally intelligent algorithms for spatial and temporal signal processing.
  • Develop computationally efficient algorithms for mapping, localization, path planning and navigational support for autonomous mobile robotics.
  • To develop embedded computational architectures based on system-on-chip methodology for real-time implementation of spatial and temporal signal processing.
  • Leverage advantages offered by reconfiguration at system-, sensor- and computational-levels for area and power-optimal designs.
  • Developing emotion recognition system for autistic children.
  • Design and development of a medical device for the assessment of vascular risk.
  • Conducting extensive research on attention levels in students, and people suffering from ADHD, and finding ways of improving it, one being Yoga, in collaboration with NIMHANS.