EVENFLOW was represented by ATHENA Research & Innovation Information Technologies (ARC) in showcasing cutting-edge research at the 2024 IEEE International Conference on Big Data (IEEE BigData ’24), held from 15 to 18 December 2024, in Washington, D.C., USA. The conference is a premier venue for advances in big data research, bringing together leading experts from around the world.

More specifically, George Klioumis, of partner ARC, presented two papers supported by the EVENFLOW project:

1. Data-driven Synchronization Protocols for Data-parallel Neural Learning over Streaming Data
   Authors: George Klioumis and Nikos Giatrakos. This work explores innovative synchronization protocols that enhance data-parallel neural learning over streaming data, addressing key challenges in scalability and efficiency.
2. A Novel Reverse Random Hyperplane Projection Scheme and Its Effect on Mining Sensor Streams. Authors: Antonios Skevis, George Klioumis, and Nikos Giatrakos. This paper introduces a novel reverse random hyperplane projection scheme, shedding light on its implications for mining sensor data streams.