Intelligent social systems marry intelligence (ability to perceive reason, learn and act) with Social Systems. The social system research is rooted in analysis of social networks pertaining to structure, network impact on human behavior and processes on networks. The research in Social Systems is complemented with research in allied areas of Machine Intelligence, Data Mining, Data Science, Pattern Recognition, Image Processing, Fuzzy Logic, Genetic Algorithms, Neural Networks, and bio- inspired computing. The domain comes under Computational Intelligence, a high priority for national research agenda. Computational intelligence (CI) is a set of nature-inspired computational methodologies which fills the gap when traditional approaches fail.
The objectives of the domain are:
- Train students and faculty in emerging areas of the domain.
- Strengthen inter-disciplinary research in areas of Social Networks, Machine Learning, Soft Computing and Image Processing.
- Research into processes, techniques, and tools to realize Intelligent Social Systems.
- Explore new areas such as Computational Science, Data Science, Computational Social Science and Nature Inspired Computing.
- Seek opportunities to collaborate with Government and Industry on projects relevant to society.
- Publish research papers in the domain.
- File Patents for any invention disclosures.
Find innovative approach to meet societal needs using state of the art research in the inter-disciplinary domain.