Collaboration with Cellular Networks for RFI Cancellation at Radio Telescope

no code implementations • 31 Oct 2022 • Shuvam Chakraborty, Gregory Hellbourg, Maqsood Careem, Dola Saha, Aveek Dutta

The growing need for electromagnetic spectrum to support the next generation (xG) communication networks increasingly generate unwanted radio frequency interference (RFI) in protected bands for radio astronomy.

Astronomy

Cyclic Imaging for All-Sky Interference Forecasting with Array Radio Telescopes

no code implementations • 26 Jul 2020 • Gregory Hellbourg, Ian Morrison

Radio Frequency Interference (RFI) is threatening modern radio astronomy.

Astronomy

Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations

no code implementations • 22 Jun 2020 • Gelu Nita, Manolis Georgoulis, Irina Kitiashvili, Viacheslav Sadykov, Enrico Camporeale, Alexander Kosovichev, Haimin Wang, Vincent Oria, Jason Wang, Rafal Angryk, Berkay Aydin, Azim Ahmadzadeh, Xiaoli Bai, Timothy Bastian, Soukaina Filali Boubrahimi, Bin Chen, Alisdair Davey, Sheldon Fereira, Gregory Fleishman, Dale Gary, Andrew Gerrard, Gregory Hellbourg, Katherine Herbert, Jack Ireland, Egor Illarionov, Natsuha Kuroda, Qin Li, Chang Liu, Yuexin Liu, Hyomin Kim, Dustin Kempton, Ruizhe Ma, Petrus Martens, Ryan McGranaghan, Edward Semones, John Stefan, Andrey Stejko, Yaireska Collado-Vega, Meiqi Wang, Yan Xu, Sijie Yu

The authors of this white paper met on 16-17 January 2020 at the New Jersey Institute of Technology, Newark, NJ, for a 2-day workshop that brought together a group of heliophysicists, data providers, expert modelers, and computer/data scientists.

BIG-bench Machine Learning Weather Forecasting