Research papers accepted by IEEE Big Data 2024

We are thrilled to announce that two of our latest research papers have been accepted to the prestigious IEEE Big Data 2024 conference!

Paper 1: LEAP: Lifelong Learning Edge-Cloud Adaptive Fused Framework for Mobility Prediction

Authors:
Newcastle University: Shamil Al-Ameen, Tejal Shah, and Rajiv Ranjan.
General Motors: Bharath Sudharsan.
University of Mosul: Roua Al-Taie.

This paper introduces LEAP, a groundbreaking framework that combines edge and cloud capabilities to enable lifelong learning for mobility prediction, paving the way for more intelligent, adaptive systems.

Paper 2: Poly Instance Recurrent Neural Network for Real-time Lifelong Learning at the Low-power Edge

Authors:
Newcastle University: Shamil Al-Ameen, Tomasz Szydlo, Tejal Shah, and Rajiv Ranjan.
General Motors: Bharath Sudharsan.
University of Limerick: Tejus Vijayakumar.

In this work, we present a novel neural network model designed to support real-time lifelong learning directly on low-power edge devices. This model is crucial for enabling efficient, always-on AI applications in resource-constrained environments.

Both projects were made possible by support from the National Edge AI Hub. The hub is dedicated to advancing AI safety and resilience in edge computing environments.

Looking forward to sharing these advancements with the IEEE Big Data 2024 community!