AN
Aditya Narendra
Uniwersytet Jagielloński w Krakowie, National Institute of Technology, Rourkela
0000-0003-1265-2981
About
I am currently (as of 2024) a doctoral student at the Jagiellonian University, Krakow, Poland. My primary research interest lies in application of machine learning techniques to astronomical data. I am currently working on estimating the redshift of Gamma-ray bursts using a machine learning technique called SuperLearner. We are focusing on getting a good estimate for the redshift using plateau emission properties of GRBs. In addition to this, I am also involved in a project where making our machine learning methodology publicly available via a webapp for anyone to use.
Employment
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Uniwersytet Jagielloński w Krakowie Doctoral Student2021 - Present
Education
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National Institute of Technology, Rourkela Integrated Master of Science, Physics and Astronomy2014 - 2019
Projects & Funding
Projects & funding information is unavailable.
Publications (13)
- Probing Evolution of Long GRB Properties through their Cosmic Formation History Aided by Machine Learning–predicted Redshifts Save
- Probing Evolution of Long Gamma-Ray Burst Properties through Their Cosmic Formation History Save
- Gamma-ray burst redshift estimation using machine learning and the associated web app Save
- GRB Redshift Estimation using Machine Learning and the Associated Web-App Save
- Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach Save
- Inferring the Redshift of More than 150 GRBs with a Machine-learning Ensemble Model Save
- GRB optical and X-ray plateau properties classifier using unsupervised machine learning Save
- Fermi LAT AGN classification using supervised machine learning Save
- A Stochastic Approach to Reconstruct Gamma-Ray-burst Light Curves Save
- Using Multivariate Imputation by Chained Equations to Predict Redshifts of Active Galactic Nuclei Save