Person
Alireza Amirshahi
Related publications (9)
Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures
David Atienza Alonso, Giovanni Ansaloni, Alireza Amirshahi
The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...
2024SzCORE: A Seizure Community Open-source Research Evaluation framework for the validation of EEG-based automated seizure detection algorithms
David Atienza Alonso, Alireza Amirshahi, Jonathan Dan, Adriano Bernini, William Cappelletti, Luca Benini, Una Pale
The need for high-quality automated seizure detection algorithms based on electroencephalography (EEG) becomes ever more pressing with the increasing use of ambulatory and long-term EEG monitoring. Heterogeneity in validation methods of these algorithms in ...
2024FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems
David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, José Angel Miranda Calero, Jonathan Dan
The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of el ...
2024M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems
David Atienza Alonso, Amir Aminifar, Tomas Teijeiro Campo, Alireza Amirshahi, Farnaz Forooghifar, Saleh Baghersalimi
Integrating low-power wearable systems into routine health monitoring is an ongoing challenge. Recent advances in the computation capabilities of wearables make it possible to target complex scenarios by exploiting multiple biosignals and using high-perfor ...
2024TiC-SAT: Tightly-coupled Systolic Accelerator for Transformers
David Atienza Alonso, Giovanni Ansaloni, Alireza Amirshahi, Joshua Alexander Harrison Klein
Transformer models have achieved impressive results in various AI scenarios, ranging from vision to natural language processing. However, their computational complexity and their vast number of parameters hinder their implementations on resource-constraine ...
2023Layer-Wise Learning Framework for Efficient DNN Deployment in Biomedical Wearable Systems
David Atienza Alonso, Amir Aminifar, Tomas Teijeiro Campo, Alireza Amirshahi, Saleh Baghersalimi
The development of low-power wearable systems requires specialized techniques to accommodate their unique requirements and constraints. While significant advancements have been made in the inference phase of artificial intelligence, the training phase rema ...
2023Predicting Survey Response with Quotation-based Modeling: A Case Study on Favorability towards the United States
Alireza Amirshahi, Saleh Baghersalimi, Jonathan Philippe Reymond
The acquisition of survey responses is a crucial component in conducting research aimed at comprehending public opinion. However, survey data collection can be arduous, time-consuming, and expensive, with no assurance of an adequate response rate. In this ...
IEEE COMPUTER SOC2023M2D2: Maximum-Mean-Discrepancy Decoder for Temporal Localization of Epileptic Brain Activities
David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, Anthony Hitchcock Thomas
Recent years have seen growing interest in leveraging deep learning models for monitoring epilepsy patients based on electroencephalographic (EEG) signals. However, these approaches often exhibit poor generalization when applied outside of the setting in w ...
2022EpilepsyGAN: Synthetic Epileptic Brain Activities with Privacy Preservation
David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, Damián Pascual Ortiz
Epilepsy is a chronic neurological disorder affecting more than 65 million people worldwide and manifested by recurrent unprovoked seizures. The unpredictability of seizures not only degrades the quality of life of the patients, but it can also be life-thr ...
2020