Niraj Welikala | Astrophysics, Cosmology & Data-Driven Modelling

Research in galaxy formation, star formation and weak-lensing systematics using ground- and space-based telescope data, image modelling, statistical inference and computational methods.

Research Overview

My research focuses on understanding how galaxies form and evolve, including the roles of star formation, environment and internal galaxy processes. I have also worked in observational cosmology through galaxy modelling for weak gravitational lensing measurements, which are used to constrain Dark Matter and Dark Energy with high precision. My work in astrophysics has combined advanced computational methods, physics-based modelling and statistical inference.

Select Research Contributions

pixel-z
Developed a method of spatially resolving stellar populations and their properties (e.g. star formation, dust and metallicity) within galaxies using broad-band colours of individual pixels - applied to thousands of galaxies in Hubble Space Telescope and ~70,000 galaxies in the Sloan Digital Sky Survey Link to paper
High redshift sub-millimetre galaxies
- Led a joint project between the ESA-NASA Planck mission and the South Pole Telescope (SPT) investigating high-redshift strongly lensed dusty star-forming galaxies, including evidence for enhanced star formation and clustering in foreground dark matter haloes Link to paper
Galaxy colour gradients and weak-lensing systematics
Led the core galaxy-modelling work for ESA Euclid mission's pre-launch control of weak-lensing systematic bias arising from galaxy colour gradients, supporting precision measurements of dark matter and dark energy. Link to paper
First Galaxies simulations
Developed spectral simulations for observations of the First Galaxies that formed in the Epoch of Reionisation (redshifts between 5-20) with the EAGLE instrument proposed for the European Extremely Large Telescope (E-ELT). Link to paper

Research & Mentorship Interests

  • Galaxy formation and evolution

  • Star formation in distant galaxies

  • Spatially resolved properties of galaxies: morphology, colour gradients, resolved stellar populations

  • Weak gravitational lensing

  • Astronomical image analysis

  • Statistical inference

  • Computational astrophysics

  • Machine learning for astronomical surveys

Education & Affiliations

  • MPhys (Oxford), Diploma in Computer Science (Cambridge), PhD Astrophysics (University of Pittsburgh, USA)

  • Honorary Fellow - University of Edinburgh

  • Builder - Euclid Collaboration

  • Fellow - Royal Astronomical Society

  • Former Beecroft Fellow in astrophysics (Oxford), former CNRS/CNES postdoctoral fellow (France)

Publications

Links:
- ADS