1 citations · 2 across the 9 of their papers we have counts for
10 papers
When Secure Aggregation Falls Short: Achieving Long-Term Privacy in Asynchronous Federated Learning for LEO Satellite Networks
Mohamed Elmahallawy, Tie Luo
Secure aggregation is a common technique in federated learning (FL) for protecting data privacy from both curious internal entities (clients or server) and external adversaries (ea…
Unlocking Neural Transparency: Jacobian Maps for Explainable AI in Alzheimer's Detection
Yasmine Mustafa, Mohamed Elmahallawy, Tie Luo
Alzheimer's disease (AD) leads to progressive cognitive decline, making early detection crucial for effective intervention. While deep learning models have shown high accuracy in A…
Efficient Brain Imaging Analysis for Alzheimer's and Dementia Detection Using Convolution-Derivative Operations
Yasmine Mustafa, Mohamed Elmahallawy, Tie Luo
Alzheimer's disease (AD) is characterized by progressive neurodegeneration and results in detrimental structural changes in human brains. Detecting these changes is crucial for ear…
Communication-Efficient Federated Learning for LEO Satellite Networks Integrated with HAPs Using Hybrid NOMA-OFDM
Mohamed Elmahallawy, Tie Luo, Khaled Ramadan
Space AI has become increasingly important and sometimes even necessary for government, businesses, and society. An active research topic under this mission is integrating federate…
Stitching Satellites to the Edge: Pervasive and Efficient Federated LEO Satellite Learning
Mohamed Elmahallawy, Tie Luo
In the ambitious realm of space AI, the integration of federated learning (FL) with low Earth orbit (LEO) satellite constellations holds immense promise. However, many challenges p…
Secure and Efficient Federated Learning in LEO Constellations using Decentralized Key Generation and On-Orbit Model Aggregation
Mohamed Elmahallawy, Tie Luo, Mohamed I. Ibrahem
Satellite technologies have advanced drastically in recent years, leading to a heated interest in launching small satellites into low Earth orbit (LEOs) to collect massive data suc…
A Brain-Computer Interface Augmented Reality Framework with Auto-Adaptive SSVEP Recognition
Yasmine Mustafa, Mohamed Elmahallawy, Tie Luo +1
Brain-Computer Interface (BCI) initially gained attention for developing applications that aid physically impaired individuals. Recently, the idea of integrating BCI with Augmented…
One-Shot Federated Learning for LEO Constellations that Reduces Convergence Time from Days to 90 Minutes
Mohamed Elmahallawy, Tie Luo
A Low Earth orbit (LEO) satellite constellation consists of a large number of small satellites traveling in space with high mobility and collecting vast amounts of mobility data su…
Optimizing Federated Learning in LEO Satellite Constellations via Intra-Plane Model Propagation and Sink Satellite Scheduling
Mohamed Elmahallawy, Tie Luo
The advances in satellite technology developments have recently seen a large number of small satellites being launched into space on Low Earth orbit (LEO) to collect massive data s…
AsyncFLEO: Asynchronous Federated Learning for LEO Satellite Constellations with High-Altitude Platforms
Mohamed Elmahallawy, Tie Luo
Low Earth Orbit (LEO) constellations, each comprising a large number of satellites, have become a new source of big data "from the sky". Downloading such data to a ground station (…