6 citations · 15 across the 4 of their papers we have counts for
5 papers
AIRMap: AI-Generated Radio Maps for Wireless Digital Twins
Ali Saeizadeh, Miead Tehrani-Moayyed, Davide Villa +4
Accurate, low-latency channel modeling is essential for real-time wireless network simulation and digital-twin applications. Traditional modeling methods like ray tracing are howev…
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…
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…
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…