301 citations · 1.5k across the 70 of their papers we have counts for
71 papers
SoK: You Find What You Seek: Rethinking Oracles, Guidance, and Input Generation in Hardware Fuzzing
G Abarajithan, Zhenghua Ma, Cristian Tirelli +4
Hardware fuzzing is an active area in security verification research, yet its industrial adoption remains in its early stages. This SoK examines which lessons from software fuzzing…
EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models
Matteo Caligiuri, Francesco Barbato, Pietro Zanuttigh +1
Recent data protection laws have accelerated the adoption of Federated Learning (FL) for privacy-preserving decentralized training. Nevertheless, increasing model sizes impose subs…
Design Rules for Extreme-Edge Scientific Computing on AI Engines
Zhenghua Ma, G Abarajithan, Dimitrios Danopoulos +3
Extreme-edge scientific applications use machine learning models to analyze sensor data and make real-time decisions. Their stringent latency and throughput requirements demand sma…
FireBridge: Cycle-Accurate Hardware + Firmware Co-Verification for Modern Accelerators
G Abarajithan, Zhenghua Ma, Francesco Restuccia +1
Hardware-firmware integration is becoming a productivity bottleneck due to the increasing complexity of accelerators, characterized by intricate memory hierarchies and firmware-int…
TinySense: Effective CSI Compression for Scalable and Accurate Wi-Fi Sensing
Toan Gian, Dung T. Tran, Viet Quoc Pham +2
With the growing demand for device-free and privacy-preserving sensing solutions, Wi-Fi sensing has emerged as a promising approach for human pose estimation (HPE). However, existi…
Semantic Multiplexing
Mohammad Abdi, Francesca Meneghello, Francesco Restuccia
Mobile devices increasingly require the parallel execution of several computing tasks offloaded at the wireless edge. Existing communication systems only support parallel transmiss…
A Reliable, Time-Predictable Heterogeneous SoC for AI-Enhanced Mixed-Criticality Edge Applications
Angelo Garofalo, Alessandro Ottaviano, Matteo Perotti +20
Next-generation mixed-criticality Systems-on-chip (SoCs) for robotics, automotive, and space must execute mixed-criticality AI-enhanced sensor processing and control workloads, ens…
AXI-REALM: Safe, Modular and Lightweight Traffic Monitoring and Regulation for Heterogeneous Mixed-Criticality Systems
Thomas Benz, Alessandro Ottaviano, Chaoqun Liang +6
The automotive industry is transitioning from federated, homogeneous, interconnected devices to integrated, heterogeneous, mixed-criticality systems (MCS). This leads to challenges…
Semantic Edge Computing and Semantic Communications in 6G Networks: A Unifying Survey and Research Challenges
Milin Zhang, Mohammad Abdi, Venkat R. Dasari +1
Semantic Edge Computing (SEC) and Semantic Communications (SemComs) have been proposed as viable approaches to achieve real-time edge-enabled intelligence in sixth-generation (6G)…
DARDA: Domain-Aware Real-Time Dynamic Neural Network Adaptation
Shahriar Rifat, Jonathan Ashdown, Francesco Restuccia
Test Time Adaptation (TTA) has emerged as a practical solution to mitigate the performance degradation of Deep Neural Networks (DNNs) in the presence of corruption/ noise affecting…
Heterogeneous Sheaf Neural Networks
Luke Braithwaite, Alessio Borgi, Gabriele Onorato +4
Heterogeneous graphs, whose nodes and edges can belong to different types and feature spaces, arise in many real-world domains, including biology, recommendation, social networks,…
Resilience and Security of Deep Neural Networks Against Intentional and Unintentional Perturbations: Survey and Research Challenges
Sazzad Sayyed, Milin Zhang, Shahriar Rifat +3
In order to deploy deep neural networks (DNNs) in high-stakes scenarios, it is imperative that DNNs provide inference robust to external perturbations - both intentional and uninte…
CGRA4ML: A Hardware/Software Framework to Implement Neural Networks for Scientific Edge Computing
G Abarajithan, Zhenghua Ma, Ravidu Munasinghe +2
The scientific community increasingly relies on machine learning (ML) for near-sensor processing, leveraging its strengths in tasks such as pattern recognition, anomaly detection,…
Toward Wireless System and Circuit Co-Design for the Internet of Self-Adaptive Things
Diptashree Das, Mohammad Abdi, Minghan Liu +2
The deployment of a growing number of devices in Internet of Things (IoT) networks implies that uninterrupted and seamless adaptation of wireless communication parameters (e.g., ca…
Resilience of Entropy Model in Distributed Neural Networks
Milin Zhang, Mohammad Abdi, Shahriar Rifat +1
Distributed deep neural networks (DNNs) have emerged as a key technique to reduce communication overhead without sacrificing performance in edge computing systems. Recently, entrop…
Stitching the Spectrum: Semantic Spectrum Segmentation with Wideband Signal Stitching
Daniel Uvaydov, Milin Zhang, Clifton Paul Robinson +3
Spectrum has become an extremely scarce and congested resource. As a consequence, spectrum sensing enables the coexistence of different wireless technologies in shared spectrum ban…
SAWEC: Sensing-Assisted Wireless Edge Computing
Khandaker Foysal Haque, Francesca Meneghello, Md. Ebtidaul Karim +1
Emerging mobile virtual reality (VR) systems will require to continuously perform complex computer vision tasks on ultra-high-resolution video frames through the execution of deep…
Sensing in Bi-Static ISAC Systems with Clock Asynchronism: A Signal Processing Perspective
Kai Wu, Jacopo Pegoraro, Francesca Meneghello +9
Integrated Sensing and Communication (ISAC) has been identified as a pillar usage scenario for the impending 6G era. Bi-static sensing, a major type of sensing in ISAC, is promisin…
TOP: Towards Open & Predictable Heterogeneous SoCs
Luca Valente, Francesco Restuccia, Davide Rossi +2
Ensuring predictability in modern real-time Systems-on-Chip (SoCs) is an increasingly critical concern for many application domains such as automotive, robotics, and industrial aut…
AXI-REALM: A Lightweight and Modular Interconnect Extension for Traffic Regulation and Monitoring of Heterogeneous Real-Time SoCs
Thomas Benz, Alessandro Ottaviano, Robert Balas +4
The increasing demand for heterogeneous functionality in the automotive industry and the evolution of chip manufacturing processes have led to the transition from federated to inte…
SplitBeam: Effective and Efficient Beamforming in Wi-Fi Networks Through Split Computing
Niloofar Bahadori, Yoshitomo Matsubara, Marco Levorato +1
Modern IEEE 802.11 (Wi-Fi) networks extensively rely on multiple-input multiple-output (MIMO) to significantly improve throughput. To correctly beamform MIMO transmissions, the acc…
SINF: Semantic Neural Network Inference with Semantic Subgraphs
A. Q. M. Sazzad Sayyed, Francesco Restuccia
This paper proposes Semantic Inference (SINF) that creates semantic subgraphs in a Deep Neural Network(DNN) based on a new Discriminative Capability Score (DCS) to drastically redu…
Wi-BFI: Extracting the IEEE 802.11 Beamforming Feedback Information from Commercial Wi-Fi Devices
Khandaker Foysal Haque, Francesca Meneghello, Francesco Restuccia
Recently, researchers have shown that the beamforming feedback angles (BFAs) used for Wi-Fi multiple-input multiple-output (MIMO) operations can be effectively leveraged as a proxy…
Adversarial Attacks to Latent Representations of Distributed Neural Networks in Split Computing
Milin Zhang, Mohammad Abdi, Jonathan Ashdown +1
Distributed deep neural networks (DNNs) have been shown to reduce the computational burden of mobile devices and decrease the end-to-end inference latency in edge computing scenari…