28 citations · 86 across the 21 of their papers we have counts for
10 papers · 1 filter
Demo: Multi-Modal Seizure Prediction System
Ali Saeizadeh, Pietro Brach del Prever, Douglas Schonholtz +5
This demo presents SeizNet, an innovative system for predicting epileptic seizures benefiting from a multi-modal sensor network and utilizing Deep Learning (DL) techniques. Epileps…
TwiNet: Connecting Real World Networks to their Digital Twins Through a Live Bidirectional Link
Clifton Paul Robinson, Andrea Lacava, Pedram Johari +2
The wireless spectrum's increasing complexity poses challenges and opportunities, highlighting the necessity for real-time solutions and robust data processing capabilities. Digita…
AI-assisted Agile Propagation Modeling for Real-time Digital Twin Wireless Networks
Ali Saeizadeh, Miead Tehrani-Moayyed, Davide Villa +6
Accurate channel modeling in real-time faces remarkable challenge due to the complexities of traditional methods such as ray tracing and field measurements. AI-based techniques hav…
A Multi-Modal Non-Invasive Deep Learning Framework for Progressive Prediction of Seizures
Ali Saeizadeh, Douglas Schonholtz, Joseph S. Neimat +2
This paper introduces an innovative framework designed for progressive (granular in time to onset) prediction of seizures through the utilization of a Deep Learning (DL) methodolog…
Open6G OTIC: A Blueprint for Programmable O-RAN and 3GPP Testing Infrastructure
Gabriele Gemmi, Michele Polese, Pedram Johari +3
Softwarized and programmable Radio Access Networks (RANs) come with virtualized and disaggregated components, increasing the supply chain robustness and the flexibility and dynamis…
Listen-While-Talking: Toward dApp-based Real-Time Spectrum Sharing in O-RAN
Rajeev Gangula, Andrea Lacava, Michele Polese +5
This demo paper presents a dApp-based real-time spectrum sharing scenario where a 5th generation (5G) base station implementing the NR stack adapts its transmission and reception s…
ColosSUMO: Evaluating Cooperative Driving Applications with Colosseum
Gabriele Gemmi, Pedram Johari, Paolo Casari +3
The quest for safer and more efficient transportation through cooperative, connected and automated mobility (CCAM) calls for realistic performance analysis tools, especially with r…
Colosseum: The Open RAN Digital Twin
Michele Polese, Leonardo Bonati, Salvatore D'Oro +11
Recent years have witnessed the Open Radio Access Network (RAN) paradigm transforming the fundamental ways cellular systems are deployed, managed, and optimized. This shift is led…
BostonTwin: the Boston Digital Twin for Ray-Tracing in 6G Networks
Paolo Testolina, Michele Polese, Pedram Johari +1
Digital twins are now a staple of wireless networks design and evolution. Creating an accurate digital copy of a real system offers numerous opportunities to study and analyze its…
SeizNet: An AI-enabled Implantable Sensor Network System for Seizure Prediction
Ali Saeizadeh, Douglas Schonholtz, Daniel Uvaydov +6
In this paper, we introduce SeizNet, a closed-loop system for predicting epileptic seizures through the use of Deep Learning (DL) method and implantable sensor networks. While phar…