Aditya Narendra

Skilled Researcher enthusiastic about supporting advancements in astronomy and astrophysics. Passionate about increasing knowledge to drive growth and needed improvements. Ready to apply knowledge and four years of experience in research. Hardworking and passionate job seeker with strong organizational skills eager to secure data scientist position. Ready to help team achieve company goals. To seek and maintain full-time position that offers professional challenges utilizing interpersonal skills, excellent time management and problem-solving skills.

• Member of the Local Organising Committee, Cosmoverse Conference, Krakow, 07/09/24 - 07/11/24
• Member of the Local Organising Committee, Particle Astrophysics Conference, Krakow, 02/13/23 - 02/16/23
• Public Outreach Speaker, Night Under The Stars (NUTS), Delivered multiple public outreach talks organized by the doctoral students of the Astronomical Observatory of Jagiellonian University, Krakow, Poland.
• Featured Speaker, American Astronomical Society Journal Author Series, Discussed my first author publication titled 'Predicting the Redshift of Gamma-ray Loud AGNs Using Supervised Machine Learning.'

• Predicting the Redshift of Gamma-Ray Loud AGNs Using Supervised Machine Learning. II, Aditya Narendra, Spencer James Gibson, Maria Giovanna Dainotti, Malgorzata Bogdan, Agnieszka Pollo, Ioannis Liodakis, Artem Poliszczuk, Enrico Rinaldi, The Astrophysical Journal Supplement Series, 259, 2, 10.3847/1538-4365/ac545a
• Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach, Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo, Vahé Petrosian, Malgorzata Bogdan, Kazunari Iwasaki, Jason Xavier Prochaska, Enrico Rinaldi, David Zhou, The Astrophysical Journal Letters, 967, 2, 10.3847/2041-8213/ad4970
• Inferring the Redshift of More than 150 GRBs with a Machine-learning Ensemble Model, Maria Giovanna Dainotti, Elias Taira, Eric Wang, Elias Lehman, Aditya Narendra, Agnieszka Pollo, Grzegorz M. Madejski, Vahe Petrosian, Malgorzata Bogdan, Apratim Dey, The Astrophysical Journal Supplement Series, 271, 1, 10.3847/1538-4365/ad1aaf
• GRB optical and X-ray plateau properties classifier using unsupervised machine learning, Shubham Bhardwaj, Maria G Dainotti, Sachin Venkatesh, Aditya Narendra, Anish Kalsi, Enrico Rinaldi, Agnieszka Pollo, Monthly Notices of the Royal Astronomical Society, 525, 4, 11/01/23, 10.1093/mnras/stad2593
• Fermi LAT AGN classification using supervised machine learning, Nathaniel Cooper, Maria Giovanna Dainotti, Aditya Narendra, Ioannis Liodakis, Malgorzata Bogdan, Monthly Notices of the Royal Astronomical Society, 525, 2, 10/01/23, 10.1093/mnras/stad2193
• Using Multivariate Imputation by Chained Equations to Predict Redshifts of Active Galactic Nuclei, Spencer James Gibson, Aditya Narendra, Maria Giovanna Dainotti, Malgorzata Bogdan, Agnieszka Pollo, Artem Poliszczuk, Enrico Rinaldi, Ioannis Liodakis, Frontiers in Astronomy and Space Sciences, 9, 03/09/22, 10.3389/fspas.2022.836215
• Predicting the redshift of gamma-ray loud AGNs using supervised machine learning, Maria Giovanna Dainotti, Malgorzata Bogdan, Aditya Narendra, Spencer James Gibson, Blazej Miasojedow, Ioannis Liodakis, Agnieszka Pollo, Trevor Nelson, Kamil Wozniak, The Astrophysical Journal, 920, 2, 10.3847/1538-4357/ac1748
• Validation of estimated cloud fraction from MERRA-2 and AIRS data using ground based observation over IAO-Hanle, Shantikumar S. Ningombam, Aditya Narendra, B.C. Bhatt, T.P. Prabhu, G.C. Anupama, Dorje Angchuk, Sonam Jorphail, Advances In Space Research, 2020, 10.1016/j.asr.2020.05.001

• Gaming
• Badminton
• Swimming
• Cycling

• Workshop on Astronomy and Astrophysics, NIT Rourkela, 2018
• Fermi Summer School, Goddard Space Flight Center, NASA, USA, 06/07/21 - 07/26/21, Virtual workshop
• DAWN Winter School, The Cosmic DAWN Center, Copenhagen, Denmark, 02/07/21 - 02/11/21, Virtual workshop
• Summer School in Statistics for Astronomers XVI, Penn State University, 06/01/21 - 06/05/21

• Seventeenth Marcell Grossman Meeting, 07/07/24 - 07/12/24, Pescara, Italy, A Stochastic Approach to Reconstruct Gamma-Ray-burst Light Curves, Gamma-ray Bursts as Distance Indicators by a Statistical Learning Approach, Co-Chaired the AI3 session
• Astroinfomatics-2023 Conference, 10/01/23 - 10/06/23, Naples, Italy, Predicting the redshift of AGNs using Superlearner
• XLI Congress of the Polish Astronomical Society, 09/11/23 - 09/15/23, Torun, Poland, A Stochastic Approach to Reconstruct Gamma-Ray-burst Light Curves
• Particle Astrophysics in Poland, 02/13/23 - 02/16/23, Krakow, Predicting the redshift of AGNs using Superlearner, Part of the local organizing committee
• 28th Young Scientists' Conference on Astronomy and Space Physics, 10/24/22 - 10/28/22, Kyiv, Ukraine, Predicting the redshift of AGNs using Superlearner, Virtual poster presentation
• 5th Cosmology school, 07/16/22 - 07/31/22, Krakow, Predicting the redshift of gamma-ray loud AGNs using supervised machine learning: Part 2
• 240th Meeting of the American Astronomical Society, 06/12/22 - 06/16/22, Pasadena, California, USA, Predicting the redshift of gamma-ray loud AGNs using supervised machine learning: Part 2, Virtual oral presentation
• SeMPowisko, 05/20/22 - 05/22/22, Krakow, Poland, Predicting the redshift of gamma-ray loud AGNs using supervised machine learning, Virtual oral presentation
• XL Polish Astronomical Society Meeting, 09/13/21 - 09/17/21, Poland, Predicting the redshift of gamma-ray loud AGNs using machine learning, Virtual poster presentation
• National Astronomical Observatory of Japan Workshop, 07/01/21, Japan, Predicting the redshift of gamma-ray loud AGN using machine learning, Virtual oral presentation
• Statistical Studies and machine learning in space science, 05/17/21 - 05/21/21, Boulder Colorado, USA, Predicting the redshift of gamma-ray loud AGNs using machine learning, Virtual oral presentation