Colosseum: Large-Scale Wireless Experimentation Through Hardware-in-the-Loop Network Emulation. - Leonardo Bonati; Pedram Johari; Michele Polese; Salvatore D'Oro; Subhramoy Mohanti; Miead Tehrani Moayyed; Davide Villa; Shweta Shrivastava; Chinenye Tassie; Kurt Yoder; Ajeet Bagga; Paresh Patel; et al. (DySPAN, 2021)

Real-world Radar and LTE Signals Dataset Collected Over-the-air in Shared CBRS Band. - Chinenye Tassie; Abdo Gaber; Vini Chaudhary; Nasim Soltani; Mauro Belgiovine; Michael Löhning; Vincent Kotzsch; Charles Schroeder; Kaushik R. Chowdhury (IEEE DataPort, 2022)

ICARUS: Learning on IQ and Cycle Frequencies for Detecting Anomalous RF Underlay Signals. - Debashri Roy; Vini Chaudhury; Chinenye Tassie; Chad M. Spooner; Kaushik R. Chowdhury (INFOCOM, 2023)

Detection of Co- Existing RF Signals in CBRS Using ML: Dataset and API-Based Collection Testbed. - Chinenye Tassie; Abdo Gaber; Vini Chaudhary; Nasim Soltani; Mauro Belgiovine; Michael Löhning; Vincent Kotzsch; Charles Schroeder; Kaushik R. Chowdhury (IEEE Commun. Mag., 2023)

Leveraging Explainable AI for Reducing Queries of Performance Indicators in Open RAN. - Chinenye Tassie; Brian Kim; Joshua Groen; Mauro Belgiovine; Kaushik R. Chowdhury (ICC, 2024)

T-PRIME: Transformer-based Protocol Identification for Machine-learning at the Edge. - Mauro Belgiovine; Joshua Groen; Miquel Sirera; Chinenye Tassie; Sage Trudeau; Stratis Ioannidis; Kaushik R. Chowdhury (INFOCOM, 2024)

T-PRIME: Transformer-based Protocol Identification for Machine-learning at the Edge. - Mauro Belgiovine; Joshua Groen; Miquel Sirera; Chinenye Tassie; Ayberk Yarkin Yildiz; Sage Trudeau; Stratis Ioannidis; Kaushik R. Chowdhury (CoRR, 2024)