Astronomical Data-modelling and Interpretation


  • Image Processing

  • Machine Learning

  • Data analysis


Mentors :

  • Jai Israni

Mentees :

  • 14


If you wish to get a flavour(yes more or less a flavour) of such techniques, find exoplanets that may support life, estimate galaxy redshifts, classify galaxies based on their visible shapes, do some image processing, then this project is meant for you.

Gone are the days when astronomers kept details of the heavens in their palm-sized journals. The Very Large Array Radio Telescope of New Mexico produces observational data at the rate of 1Tb/s or 36000Tb per night. To tackle these numbers, we develop intricate algorithms.

If you wish to get a flavour(yes more or less a flavour) of such techniques, find exoplanets that may support life, estimate galaxy redshifts, classify galaxies based on their visible shapes, do some image processing, then this project is meant for you. We follow methods that are way beyond conventional numerical techniques (that don’t work efficiently with modern data). The project involves learning for both astrophysics enthusiasts as well as lots of coding for programmers, and needless to mention it’s a mix of both for absolute beginners!

Tentative Timeline :

Week Number Tasks to be Completed
Week 1 Brushing up with Python
Week 2 Pulsar detection, Cross-matching astronomical catalogues
Week 3 Predicting and Classifying exoplanets, learning SQL
Week 4 Galaxy classification and estimating galaxy redshifts using regression
Week 5 Test of overall understanding