5 citations · 14 across the 20 of their papers we have counts for
21 papers
MANE: A Multi-Path Adaptive Network for Edge Onloading of Deep Neural Networks
Sokratis Nikolaidis, Stylianos I. Venieris, Leonidas Malachias +1
Split computing constitutes a widely used distributed inference approach, where a lightweight head model is onloaded onto the device and a heavier tail model resides on an edge ser…
A-THENA: Early Intrusion Detection for IoT with Time-Aware Hybrid Encoding and Network-Specific Augmentation
Ioannis Panopoulos, Maria Lamprini A. Bartsioka, Sokratis Nikolaidis +3
The proliferation of Internet of Things (IoT) devices has significantly expanded attack surfaces, making IoT ecosystems particularly susceptible to sophisticated cyber threats. To…
Federated Learning-driven Beam Management in LEO 6G Non-Terrestrial Networks
Maria Lamprini Bartsioka, Ioannis A. Bartsiokas, Athanasios D. Panagopoulos +2
Low Earth Orbit (LEO) Non-Terrestrial Networks (NTNs) require efficient beam management under dynamic propagation conditions. This work investigates Federated Learning (FL)-based b…
FRIEND: Federated Learning for Joint Optimization of multi-RIS Configuration and Eavesdropper Intelligent Detection in B5G Networks
Maria Lamprini A. Bartsioka, Ioannis A. Bartsiokas, Anastasios K. Papazafeiropoulos +3
As wireless systems evolve toward Beyond 5G (B5G), the adoption of cell-free (CF) millimeter-wave (mmWave) architectures combined with Reconfigurable Intelligent Surfaces (RIS) is…
Flexible Intelligent Metasurface for Downlink Communications under Statistical CSI
Vaibhav Kumar, Anastasios Papazafeiropoulos, Pandelis Kourtessis +4
Flexible intelligent metasurface (FIM) is a recently developed, groundbreaking hardware technology with promising potential for 6G wireless systems. Unlike conventional rigid anten…
On the Ergodic Capacity for SIM-Aided Holographic MIMO Communications
Anastasios Papazafeiropoulos, Ioannis Bartsiokas, Dimitra I. Kaklamani +1
We derive a novel closed-form lower bound on the ergodic capacity of holographic multiple-input multiple-output (HMIMO) systems enhanced by stacked intelligent metasurfaces (SIMs)…
Ergodic Mutual Information and Outage Probability for SIM-Assisted Holographic MIMO Communications
Anastasios Papazafeiropoulos, Pandelis Kourtessis, Dimitra I. Kaklamani +1
Stacked intelligent metasurface (SIM) is a promising enabler for next-generation high-capacity networks that exhibit better performance compared to its single-layer counterpart by…
Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT
Ioannis Panopoulos, Maria-Lamprini A. Bartsioka, Sokratis Nikolaidis +3
The rapid expansion of the Internet of Things (IoT) has introduced significant security challenges, necessitating efficient and adaptive Intrusion Detection Systems (IDS). Traditio…
ML-Enabled Eavesdropper Detection in Beyond 5G IIoT Networks
Maria-Lamprini A. Bartsioka, Ioannis A. Bartsiokas, Panagiotis K. Gkonis +2
Advanced fifth generation (5G) and beyond (B5G) communication networks have revolutionized wireless technologies, supporting ultra-high data rates, low latency, and massive connect…
Channel Estimation for Stacked Intelligent Metasurfaces in Rician Fading Channels
Anastasios Papazafeiropoulos, Pandelis Kourtessis, Dimitra I. Kaklamani +1
The recent combination of the rising architectures, known as stacked intelligent metasurface (SIM) and holographic multiple-input multiple-output (HMIMO), drives toward breakthroug…
STARS-Enabled Full-Duplex Two-Way mMIMO System Under Spatially-Correlated Channels
Anastasios Papazafeiropoulos, Pandelis Kourtessis, Symeon Chatzinotas +2
\underline{S}imultaneous \underline{t}ransmitting \underline{a}nd \underline{r}eflecting \underline{s}urface (STARS)-assisted systems have emerged to fill this gap by providing $ 3…
MultiTASC++: A Continuously Adaptive Scheduler for Edge-Based Multi-Device Cascade Inference
Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris
Cascade systems, consisting of a lightweight model processing all samples and a heavier, high-accuracy model refining challenging samples, have become a widely-adopted distributed…
CARIn: Constraint-Aware and Responsive Inference on Heterogeneous Devices for Single- and Multi-DNN Workloads
Ioannis Panopoulos, Stylianos I. Venieris, Iakovos S. Venieris
The relentless expansion of deep learning applications in recent years has prompted a pivotal shift toward on-device execution, driven by the urgent need for real-time processing,…
Near-Field Beamforming for Stacked Intelligent Metasurfaces-assisted MIMO Networks
Anastasios Papazafeiropoulos, Pandelis Kourtessis, Symeon Chatzinotas +2
Stacked intelligent metasurfaces (SIMs) have recently gained significant interest since they enable precoding in the wave domain that comes with increased processing capability and…
Achievable Rate Optimization for Large Stacked Intelligent Metasurfaces Based on Statistical CSI
Anastasios Papazafeiropoulos, Pandelis Kourtessis, Symeon Chatzinotas +2
Stacked intelligent metasurface (SIM) is an emerging design that consists of multiple layers of metasurfaces. A SIM enables holographic multiple-input multiple-output (HMIMO) preco…
Performance of Double-Stacked Intelligent Metasurface-Assisted Multiuser Massive MIMO Communications in the Wave Domain
Anastasios Papazafeiropoulos, Pandelis Kourtessis, Symeon Chatzinotas +2
Although reconfigurable intelligent surface (RIS) is a promising technology for shaping the propagation environment, it consists of a single-layer structure within inherent limitat…
MultiTASC: A Multi-Tenancy-Aware Scheduler for Cascaded DNN Inference at the Consumer Edge
Sokratis Nikolaidis, Stylianos I. Venieris, Iakovos S. Venieris
Cascade systems comprise a two-model sequence, with a lightweight model processing all samples and a heavier, higher-accuracy model conditionally refining harder samples to improve…
Exploring the Performance and Efficiency of Transformer Models for NLP on Mobile Devices
Ioannis Panopoulos, Sokratis Nikolaidis, Stylianos I. Venieris +1
Deep learning (DL) is characterised by its dynamic nature, with new deep neural network (DNN) architectures and approaches emerging every few years, driving the field's advancement…
How to Reach Real-Time AI on Consumer Devices? Solutions for Programmable and Custom Architectures
Stylianos I. Venieris, Ioannis Panopoulos, Ilias Leontiadis +1
The unprecedented performance of deep neural networks (DNNs) has led to large strides in various Artificial Intelligence (AI) inference tasks, such as object and speech recognition…
OODIn: An Optimised On-Device Inference Framework for Heterogeneous Mobile Devices
Stylianos I. Venieris, Ioannis Panopoulos, Iakovos S. Venieris
Radical progress in the field of deep learning (DL) has led to unprecedented accuracy in diverse inference tasks. As such, deploying DL models across mobile platforms is vital to e…
PerceptionNet: A Deep Convolutional Neural Network for Late Sensor Fusion
Panagiotis Kasnesis, Charalampos Z. Patrikakis, Iakovos S. Venieris
Human Activity Recognition (HAR) based on motion sensors has drawn a lot of attention over the last few years, since perceiving the human status enables context-aware applications…