Hossein Ahmadi

Ph.D. candidate in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 38^th cycle (2022-2025)
Department of Electronics and Telecommunications (DET)

hossein.ahmadi@polito.it

Profile

PhD

Research topic

Brain-to-Brain Communication based on Semantic Features in EEG Signals

Tutors

Luca Mesin
Ali Kuhestani

Research presentation

Research interests

Multimedia Signal Processing

Optical and Wireless Digital Transmissions Systems

Big Data, Machine Learning, Neural Networks and Data Science

Biomedical devices and applications

Biography

I am an experienced academic with a Master's in Telecommunication Engineering from Amirkabir University of Technology, Tehran, Iran. My research interests include Brain-to-Brain Communication, Semantic Communication, Brain-Computer Interface, and Semantic Feature Extraction from EEG Signals. I have a robust teaching background and significant industry experience.

Research

Research groups

Mathematical Biology and Physiology (DET)

Publications

Latest publications View all publications in Porto@Iris

Ahmadi, Hossein; Mesin, Luca (2025)
Universal semantic feature extraction from EEG signals: a task-independent framework. In: JOURNAL OF NEURAL ENGINEERING, vol. 22. ISSN 1741-2560
Contributo su Rivista
Ahmadi, Hossein; Kuhestani, Ali; Keshavarzi, Mohammadreza; Mesin, Luca (2025)
Securing Brain-to-Brain Communication Channels Using Adversarial Training on SSVEP EEG. In: IEEE ACCESS, vol. 13, pp. 14358-14378. ISSN 2169-3536
Contributo su Rivista
Ahmadi, Hossein; Mesin, Luca (2024)
Enhancing MI EEG Signal Classification With a Novel Weighted and Stacked Adaptive Integrated Ensemble Model: A Multi-Dataset Approach. In: IEEE ACCESS, vol. 12, pp. 103626-103646. ISSN 2169-3536
Contributo su Rivista
Ahmadi, H.; Kuhestani, A.; Mesin, L. (2024)
Adversarial Neural Network Training for Secure and Robust Brain-to-Brain Communication. In: IEEE ACCESS, vol. 12, pp. 39450-39469. ISSN 2169-3536
Contributo su Rivista
Ahmadi, Hossein; Mesin, Luca (2024)
Enhancing Motor Imagery Electroencephalography Classification with a Correlation-Optimized Weighted Stacking Ensemble Model. In: ELECTRONICS, vol. 13. ISSN 2079-9292
Contributo su Rivista