Data Science & Mathematics
  • Use of techniques from differential equations (ordinary or partial), random processes, etc. to model phenomena in meteorology, oceanography, environmental sciences, epidemiology, geophysics, etc. with accompanying analysis and/or numerical or simulation techniques.
  • Application of statistical methodologies to medicine, weather prediction, disaster prediction (e.g., earthquakes), environment, and so on.
  • Application of algebra, algebraic geometry, number theory, etc. to problems relevant to national security such as coding theory and cryptography.
  • Application of statistical methodologies and optimization in logistics applied to areas such as defence, disaster management, etc.
  • Development of provably effective algorithms for analysis of large data sets of social relevance such as in problems of resource allocation.
  • Application of dynamical systems and control theory to robotics, aerospace engineering, etc.
  • Applications to medicine (medical image analysis, tomography, dosage optimization)
  • Modelling and analysis for meteorology, oceanography etc., (monsoon modelling, disaster prediction)

This list is suggestive and not exhaustive. The projects are required to be translational, in the sense that the research should demonstrably lead to concrete results in the domain for which the application is intended and not merely be an 'in principle' or 'proof of concept' result. At the same time, it should not be a routine application of existing techniques.


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