ILDS (Interdisciplinary Laboratory for Data Science)

This research initiative seeks to advance and implement practices for gathering, processing and analysing data across different engineering and social branches. The primary aim of the initiative is to be one-stop-solution for all data analytics related needs — gathering, processing and analysing — of the IIT community as well as the larger Indian eco-system. The initiative will initially focus on analytics related to the establishment of smart cities. We will specifically focus on studies related to smart transportation, smart grids and smart water supply. The initiative will also setup physical infrastructure and the establish standard operating practices pertaining to Data Science, leading to development of broad competence in the area of data sciences across various related disciplines.
We work closely with several industry partners and government agencies to develop cutting edge solutions to real problems. There are three critical areas of research impact in this study. The first one is the area of Data Analytics− Data mining/Machine learning, Network analysis, Optimisation, Design of Experiments, etc. The second, is in the advancement of data gathering and processing related infrastructure – sensing, storage, and computing – paying special attention to secure computing systems. The third and equally important target, is contribution to domain specific advances in academic disciplines where empirical research has the potential to supplement the respective body of knowledge. The scope of this research is therefore multi-disciplinary in nature and will build on and contribute to a wide range of domains and functional applications.
Faculty from the department (Arun Tangirala, Nirav Bhatt, Raghunathan Rengaswamy, Shankar Narasimhan, Sridharakumar Narasimhan) are actively involved with ILDS contributing to methods, algorithms for data science and domain areas in smart grids and water supply.
A new interdisciplinary dual degree specialization in data science open to students from all disciplines is to be introduced from this academic year. ​ Faculty from chemical engineering are actively involved in this programme. In addition to existing courses on multivariate statistics, time series analysis and system identification, new courses on foundations for data science, artificial Intelligence in process engineering and manufacturing analytics will be offered by faculty from chemical engineering.


Dr. Sridharakumar Narasimhan